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  <title>Track Awesome Machine Learning Updates Weekly</title>
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  <updated>2026-04-22T03:37:35.036Z</updated>
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  <subtitle>A curated list of awesome Machine Learning frameworks, libraries and software.</subtitle>
  <entry>
    <id>https://www.trackawesomelist.com/2026/17/</id>
    <title>Awesome Machine Learning Updates on Apr 27 - May 03, 2026</title>
    <updated>2026-04-22T03:37:35.036Z</updated>
    <published>2026-04-22T03:37:34.987Z</published>
    <content type="html"><![CDATA[<h3><p>IMPORTANT NOTE ON PRs:</p>
</h3>
<ul>
<li>Repository's owner explicitly says that "this library is not maintained".</li>
</ul>

<ul>
<li>Not committed for a long time (2~3 years).</li>
</ul>

<ul>
<li>For a list of free machine learning books available for download, go <a href="https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md" rel="noopener noreferrer">here (⭐72k)</a>.</li>
</ul>

<ul>
<li>For a list of professional machine learning events, go <a href="https://github.com/josephmisiti/awesome-machine-learning/blob/master/events.md" rel="noopener noreferrer">here (⭐72k)</a>.</li>
</ul>

<ul>
<li>For a list of (mostly) free machine learning courses available online, go <a href="https://github.com/josephmisiti/awesome-machine-learning/blob/master/courses.md" rel="noopener noreferrer">here (⭐72k)</a>.</li>
</ul>

<ul>
<li>For a list of blogs and newsletters on data science and machine learning, go <a href="https://github.com/josephmisiti/awesome-machine-learning/blob/master/blogs.md" rel="noopener noreferrer">here (⭐72k)</a>.</li>
</ul>

<ul>
<li>For a list of free-to-attend meetups and local events, go <a href="https://github.com/josephmisiti/awesome-machine-learning/blob/master/meetups.md" rel="noopener noreferrer">here (⭐72k)</a>.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2026/17/"/>
    <summary>7 awesome projects updated on Apr 27 - May 03, 2026</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2026/15/</id>
    <title>Awesome Machine Learning Updates on Apr 13 - Apr 19, 2026</title>
    <updated>2026-04-12T03:43:23.591Z</updated>
    <published>2026-04-12T03:43:23.591Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/Yigtwxx/Awesome-RAG-Production" rel="noopener noreferrer">Awesome RAG Production (⭐27)</a> - A curated collection of battle-tested tools, frameworks, and best practices for building, scaling, and monitoring production-grade Retrieval-Augmented Generation (RAG) systems. Covers frameworks, vector databases, retrieval &amp; reranking, evaluation, observability, deployment, and security.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2026/15/"/>
    <summary>1 awesome projects updated on Apr 13 - Apr 19, 2026</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2026/12/</id>
    <title>Awesome Machine Learning Updates on Mar 23 - Mar 29, 2026</title>
    <updated>2026-03-16T03:31:42.297Z</updated>
    <published>2026-03-16T03:31:40.526Z</published>
    <content type="html"><![CDATA[<h3><p>C / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://qsmm.org" rel="noopener noreferrer">qsmm</a> - A C library implementing the rudiments of a toolchain for working with adaptive probabilistic assembler programs.</li>
</ul>
<h3><p>C / Computer Vision</p>
</h3>
<ul>
<li><a href="https://specx.pro" rel="noopener noreferrer">SpecX</a> - Specialized AI vision for extracting engineering specs from PDF/JPG to Excel.</li>
</ul>
<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/facebookincubator/MCGrad/" rel="noopener noreferrer">MCGrad (⭐27)</a> - A production-ready library for multicalibration, fairness, and bias correction in machine learning models.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/clearml/clearml" rel="noopener noreferrer">ClearML (⭐6.6k)</a> -  Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling &amp; Serving in one MLOps/LLMOps solution.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://gpuperhour.com" rel="noopener noreferrer">GPU Per Hour</a> - Real-time GPU cloud price comparison across 30+ providers.</li>
</ul>

<ul>
<li><a href="https://github.com/darfaz/clawmoat" rel="noopener noreferrer">ClawMoat (⭐38)</a> - Open-source runtime security scanner for AI agents. Detects prompt injection, jailbreak, PII leakage, memory poisoning, and tool misuse. Zero deps, MIT licensed.</li>
</ul>

<ul>
<li><a href="https://github.com/RunanywhereAI/runanywhere-sdks" rel="noopener noreferrer">RunAnywhere (⭐10k)</a> - Open-source SDK for running LLMs and multimodal models on-device across iOS, Android, and cross-platform apps.</li>
</ul>

<ul>
<li><a href="https://github.com/vuics/h9y" rel="noopener noreferrer">HyperAgency (⭐34)</a> - agentic AI operating system (h9y.ai) that replaces brittle/fragmented automations with long-lived, self-improving systems. Open-source, self-hosted/cloud, visual workflow, omni-channel, decentralized, extensible.</li>
</ul>

<ul>
<li><a href="https://github.com/Bread-Technologies/mle_vscode_extension" rel="noopener noreferrer">Bread Dataset Viewer (⭐3)</a> - A VS Code extension for viewing and exploring large machine learning datasets (CSV, JSON, Parquet, etc.) directly within the editor without VS Code crashing in a clean UI.</li>
</ul>

<ul>
<li><a href="https://github.com/Bread-Technologies/bread_wandb_viewer_extension" rel="noopener noreferrer">Bread WandB Viewer (⭐4)</a> - A VS Code extension to view Weights &amp; Biases experiments, logs, and artifacts within the IDE, eliminating the need to switch to the web UI and keeping data private.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2026/12/"/>
    <summary>10 awesome projects updated on Mar 23 - Mar 29, 2026</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2026/5/</id>
    <title>Awesome Machine Learning Updates on Feb 02 - Feb 08, 2026</title>
    <updated>2026-01-30T02:49:55.873Z</updated>
    <published>2026-01-30T02:49:55.873Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/final-kk/kandle" rel="noopener noreferrer">Kandle (⭐7)</a> - A JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2026/5/"/>
    <summary>1 awesome projects updated on Feb 02 - Feb 08, 2026</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2026/1/</id>
    <title>Awesome Machine Learning Updates on Jan 05 - Jan 11, 2026</title>
    <updated>2026-01-03T02:19:32.746Z</updated>
    <published>2026-01-03T02:19:30.777Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><ul>
<li><a href="https://github.com/kayba-ai/agentic-context-engine" rel="noopener noreferrer">Agentic Context Engine (⭐2.2k)</a> -In-context learning framework that allows agents to learn from execution feedback.</li>
</ul>
</li>
</ul>

<ul>
<li><a href="https://github.com/nndeploy/nndeploy" rel="noopener noreferrer">nndeploy (⭐1.8k)</a> - An Easy-to-Use and High-Performance AI deployment framework.</li>
</ul>
<h3><p>CUDA PTX / Neurosymbolic AI</p>
</h3>
<ul>
<li><a href="https://github.com/danielcamposramos/Knowledge3D" rel="noopener noreferrer">Knowledge3D (K3D) (⭐34)</a> - Sovereign GPU-native spatial AI architecture with PTX-first cognitive engine (RPN/TRM reasoning), tri-modal fusion (text/visual/audio), and 3D persistent memory ("Houses"). Features sub-100µs inference, procedural knowledge compression (69:1 ratio), and multi-agent swarm architecture. Zero external dependencies for core inference paths.</li>
</ul>
<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/hissain/jscipy" rel="noopener noreferrer">jSciPy (⭐19)</a> - A Java port of SciPy's signal processing module, offering filters, transformations, and other scientific computing utilities.</li>
</ul>
<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/nguyenphuminh/catniff" rel="noopener noreferrer">Catniff (⭐9)</a> - Torch-like deep learning framework for Javascript with support for tensors, autograd, optimizers, and other neural net constructs.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://gempix2.site" rel="noopener noreferrer">Gempix2</a> - Free production platform for text-to-image generation using Nano Banana V2 model.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/nobodywho-ooo/nobodywho" rel="noopener noreferrer">NobodyWho (⭐799)</a> - The simplest way to run an LLM locally. Supports tool calling and grammar constrained sampling.</li>
</ul>

<ul>
<li><a href="https://github.com/bibinprathap/VeritasGraph" rel="noopener noreferrer">VeritasGraph (⭐269)</a> - Enterprise-Grade Graph RAG for Secure, On-Premise AI with Verifiable Attribution.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/interpretml/interpret" rel="noopener noreferrer">InterpretML (⭐6.8k)</a> - InterpretML implements the Explainable Boosting Machine (EBM), a modern, fully interpretable machine learning model based on Generalized Additive Models (GAMs). This open-source package also provides visualization tools for EBMs, other glass-box models, and black-box explanations.</li>
</ul>

<ul>
<li><a href="https://github.com/juspay/neurolink" rel="noopener noreferrer">Neurolink (⭐84)</a> - Enterprise-grade LLM integration framework for building production-ready AI applications with built-in hallucination prevention, RAG, and MCP support.</li>
</ul>
<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/abkmystery/ANEE" rel="noopener noreferrer">ANEE (⭐1)</a> - Adaptive Neural Execution Engine for transformers. Per-token sparse inference with dynamic layer skipping, profiler-based gating, and KV-cache-safe compute reduction.</li>
</ul>
<h3><p>Python / Development Tools</p>
</h3>
<ul>
<li><a href="https://www.codeflash.ai/" rel="noopener noreferrer">CodeFlash.AI</a> – CodeFlash.AI – Ship Blazing-Fast Python Code, Every Time.</li>
</ul>
<h3><p>Rust / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/Michael-A-Kuykendall/shimmy" rel="noopener noreferrer">shimmy (⭐4.6k)</a> - Python-free Rust inference server for NLP models with OpenAI API compatibility and hot model swapping.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/deepnote/deepnote" rel="noopener noreferrer">Deepnote (⭐2.8k)</a> - Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps.</li>
</ul>

<ul>
<li><a href="https://github.com/promptfoo/promptfoo" rel="noopener noreferrer">promptfoo (⭐21k)</a> - Open-source LLM evaluation and red teaming framework. Test prompts, models, agents, and RAG pipelines. Run adversarial attacks (jailbreaks, prompt injection) and integrate security testing into CI/CD.</li>
</ul>

<ul>
<li><a href="https://github.com/Agent-Field/agentfield" rel="noopener noreferrer">Agentfield (⭐1.5k)</a> - Open source Kubernetes-style control plane for deploying AI agents as distributed microservices, with built-in service discovery, durable workflows, and observability.</li>
</ul>

<ul>
<li><a href="https://github.com/MervinPraison/PraisonAI" rel="noopener noreferrer">PraisonAI (⭐7k)</a> - Production-ready Multi-AI Agents framework with self-reflection. Fastest agent instantiation (3.77μs), 100+ LLM support via LiteLLM, MCP integration, agentic workflows (route/parallel/loop/repeat), built-in memory, Python &amp; JS SDKs.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2026/1/"/>
    <summary>17 awesome projects updated on Jan 05 - Jan 11, 2026</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2025/44/</id>
    <title>Awesome Machine Learning Updates on Nov 03 - Nov 09, 2025</title>
    <updated>2025-10-29T02:16:39.694Z</updated>
    <published>2025-10-29T02:16:39.694Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><ul>
<li><a href="https://topfreeprompts.com" rel="noopener noreferrer">TopFreePrompts by LucyBrain</a> -&gt; 10,000+ professional AI prompts across 23 categories with systematic training for automating ML workflows and analysis.</li>
</ul>
</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2025/44/"/>
    <summary>1 awesome projects updated on Nov 03 - Nov 09, 2025</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2025/41/</id>
    <title>Awesome Machine Learning Updates on Oct 13 - Oct 19, 2025</title>
    <updated>2025-10-07T01:58:47.086Z</updated>
    <published>2025-10-07T01:58:46.164Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://ray3.run" rel="noopener noreferrer">ray3.run</a> - AI-powered tools and applications for developers and businesses to enhance productivity and workflow automation. * <a href="https://pypi.org/project/xad/" rel="noopener noreferrer">XAD</a> -&gt; Fast and easy-to-use backpropagation tool.</li>
</ul>

<ul>
<li><a href="https://github.com/doobidoo/mcp-memory-service" rel="noopener noreferrer">MCP Memory Service (⭐1.7k)</a> - Universal memory service with semantic search, autonomous consolidation, and multi-client support for AI applications.</li>
</ul>

<ul>
<li><a href="https://github.com/momonga-ml/gower-express.git" rel="noopener noreferrer">Gower Express</a> - The Fastest Gower Distance Implementation for Python. GPU-accelerated similarity matching for mixed data types, 15-25% faster than alternatives with production-ready reliability.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/code-forge-temple/agentic-signal" rel="noopener noreferrer">Agentic Signal (⭐147)</a> - Visual AI agent workflow automation platform with local LLM integration. Build intelligent workflows using drag-and-drop, no cloud required.</li>
</ul>

<ul>
<li><a href="https://github.com/code-forge-temple/scribe-pal" rel="noopener noreferrer">ScribePal (⭐22)</a> - Chrome extension that uses local LLMs to assist with writing and drafting responses based on the context of your open tabs.</li>
</ul>

<ul>
<li><a href="https://github.com/code-forge-temple/local-llm-npc" rel="noopener noreferrer">Local LLM NPC (⭐46)</a> - Godot 4.x asset that enables NPCs to interact with players using local LLMs for structured, offline-first learning conversations in games.</li>
</ul>

<ul>
<li><a href="https://github.com/JehoshuaM/awesome-huggingface-models" rel="noopener noreferrer">Awesome Hugging Face Models (⭐10)</a> - Curated list of top Hugging Face models for NLP, vision, and audio tasks with demos and benchmarks.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2025/41/"/>
    <summary>7 awesome projects updated on Oct 13 - Oct 19, 2025</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2025/33/</id>
    <title>Awesome Machine Learning Updates on Aug 18 - Aug 24, 2025</title>
    <updated>2025-08-14T02:22:02.063Z</updated>
    <published>2025-08-14T02:22:00.742Z</published>
    <content type="html"><![CDATA[<h3><p>C / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/onnx/onnx-c" rel="noopener noreferrer">onnx-c</a> - A lightweight C library for ONNX model inference, optimized for performance and portability across platforms.</li>
</ul>
<h3><p>C / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/ultralytics/ultralytics" rel="noopener noreferrer">YOLOv8 (⭐56k)</a> - Ultralytics' YOLOv8 implementation with C++ support for real-time object detection and tracking, optimized for edge devices.</li>
</ul>
<h3><p>C++ / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/google/sentencepiece" rel="noopener noreferrer">SentencePiece (⭐12k)</a> - A C++ library for unsupervised text tokenization and detokenization, widely used in modern NLP models.</li>
</ul>
<h3><p>C++ / Speech Recognition</p>
</h3>
<ul>
<li><a href="https://github.com/alphacep/vosk-api" rel="noopener noreferrer">Vosk (⭐15k)</a> - An offline speech recognition toolkit with C++ support, designed for low-resource devices and multiple languages.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/dhgefergfefruiwefhjhcduc/ML_Forgex" rel="noopener noreferrer">mlforgex (⭐0)</a> - Lightweight ML utility for automated training, evaluation, and prediction with CLI and Python API support.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/ahoynodnarb/minidiff" rel="noopener noreferrer">minidiff (⭐2)</a> - A slightly larger, somewhat feature-complete, PyTorch-inspired, NumPy implementation of a tensor reverse-mode automatic differentiation engine.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2025/33/"/>
    <summary>6 awesome projects updated on Aug 18 - Aug 24, 2025</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2025/26/</id>
    <title>Awesome Machine Learning Updates on Jun 30 - Jul 06, 2025</title>
    <updated>2025-06-26T02:20:08.038Z</updated>
    <published>2025-06-26T02:20:08.038Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/feature-engine/feature_engine" rel="noopener noreferrer">Feature-engine (⭐2.2k)</a> - Open source library with an exhaustive battery of feature engineering and selection methods based on pandas and scikit-learn.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2025/26/"/>
    <summary>1 awesome projects updated on Jun 30 - Jul 06, 2025</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2025/25/</id>
    <title>Awesome Machine Learning Updates on Jun 23 - Jun 29, 2025</title>
    <updated>2025-06-17T02:20:43.428Z</updated>
    <published>2025-06-17T02:20:42.008Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/ozguraslank/flexml" rel="noopener noreferrer">FlexML (⭐28)</a> - Easy-to-use and flexible AutoML library for Python.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/lightly-ai/lightly-train" rel="noopener noreferrer">LightlyTrain (⭐1.4k)</a> - Pretrain computer vision models on unlabeled data for industrial applications</li>
</ul>
<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Daveonwave/gym4ReaL" rel="noopener noreferrer">Gym4ReaL (⭐48)</a> - Gym4ReaL is a comprehensive suite of realistic environments designed to support the development and evaluation of RL algorithms that can operate in real-world scenarios. The suite includes a diverse set of tasks exposing RL algorithms to a variety of practical challenges.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2025/25/"/>
    <summary>3 awesome projects updated on Jun 23 - Jun 29, 2025</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2025/22/</id>
    <title>Awesome Machine Learning Updates on Jun 02 - Jun 08, 2025</title>
    <updated>2025-05-27T02:08:55.077Z</updated>
    <published>2025-05-27T02:08:53.719Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/TSavo/creatify-mcp" rel="noopener noreferrer">Creatify MCP (⭐21)</a> - Model Context Protocol server that exposes Creatify AI's video generation capabilities to AI assistants, enabling natural language video creation workflows.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/skrub-data/skrub" rel="noopener noreferrer">skrub (⭐1.6k)</a> - Skrub is a Python library that eases preprocessing and feature engineering for machine learning on dataframes.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://localforge.dev/" rel="noopener noreferrer">Localforge</a> – Is an <a href="https://github.com/rockbite/localforge" rel="noopener noreferrer">open source (⭐365)</a> on-prem AI coding autonomous assistant that lives inside your repo, edits and tests files at SSD speed. Think Claude Code but with UI. plug in any LLM (OpenAI, Gemini, Ollama, etc.) and let it work for you.</li>
</ul>

<ul>
<li><a href="https://getmaxim.ai" rel="noopener noreferrer">Maxim AI</a> - The agent simulation, evaluation, and observability platform helping product teams ship their AI applications with the quality and speed needed for real-world use.</li>
</ul>

<ul>
<li><a href="https://github.com/splx-ai/agentic-radar" rel="noopener noreferrer">Agentic Radar (⭐951)</a> -  Open-source CLI security scanner for agentic workflows. Scans your workflow’s source code, detects vulnerabilities, and generates an interactive visualization along with a detailed security report. Supports LangGraph, CrewAI, n8n, OpenAI Agents, and more.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2025/22/"/>
    <summary>5 awesome projects updated on Jun 02 - Jun 08, 2025</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2025/15/</id>
    <title>Awesome Machine Learning Updates on Apr 14 - Apr 20, 2025</title>
    <updated>2025-04-13T03:28:46.673Z</updated>
    <published>2025-04-13T03:28:44.821Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://www.comet.com/site/products/opik/" rel="noopener noreferrer">Opik</a> - Open source engineering platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. (<a href="https://github.com/comet-ml/opik/" rel="noopener noreferrer">Source Code (⭐19k)</a>)</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/vortico/flama" rel="noopener noreferrer">Flama (⭐288)</a> - Ignite your models into blazing-fast machine learning APIs with a modern framework.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://www.fiddler.ai" rel="noopener noreferrer">Fiddler AI</a> - The all-in-one AI Observability and Security platform for responsible AI. It provides monitoring, analytics, and centralized controls to operationalize ML, GenAI, and LLM applications with trust. Fiddler helps enterprises scale LLM and ML deployments to deliver high performance AI, reduce costs, and be responsible in governance.</li>
</ul>
<h3><p>Books / Misc</p>
</h3>
<ul>
<li><a href="https://www.appliedaicourse.com/blog/machine-learning-books/" rel="noopener noreferrer">Machine Learning Books for Beginners</a> - This blog provides a curated list of introductory books to help aspiring ML professionals to grasp foundational machine learning concepts and techniques.</li>
</ul>

<ul>
<li><a href="https://pollinations.ai" rel="noopener noreferrer">Pollinations.AI</a> - Free, no-signup APIs for text, image, and audio generation with no API keys required. Offers OpenAI-compatible interfaces and React hooks for easy integration.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2025/15/"/>
    <summary>5 awesome projects updated on Apr 14 - Apr 20, 2025</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2025/7/</id>
    <title>Awesome Machine Learning Updates on Feb 17 - Feb 23, 2025</title>
    <updated>2025-02-14T01:51:58.697Z</updated>
    <published>2025-02-14T01:51:57.631Z</published>
    <content type="html"><![CDATA[<h3><p>Julia / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/clugen/CluGen.jl/" rel="noopener noreferrer">CluGen (⭐8)</a> - Multidimensional cluster generation in Julia.</li>
</ul>
<h3><p>Matlab / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/clugen/MOCluGen/" rel="noopener noreferrer">MOCluGen (⭐5)</a> - Multidimensional cluster generation in MATLAB/Octave.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/alinapetukhova/textcl" rel="noopener noreferrer">TextCL (⭐12)</a> - Text preprocessing package for use in NLP tasks.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/skforecast/skforecast" rel="noopener noreferrer">skforecast (⭐1.5k)</a> - Python library for time series forecasting using machine learning models. It works with any regressor compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others.</li>
</ul>

<ul>
<li><a href="https://github.com/clugen/pyclugen" rel="noopener noreferrer">pyclugen (⭐10)</a> - Multidimensional cluster generation in Python.</li>
</ul>
<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/clugen/clugenr/" rel="noopener noreferrer">clugenr (⭐5)</a> - Multidimensional cluster generation in R.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2025/7/"/>
    <summary>6 awesome projects updated on Feb 17 - Feb 23, 2025</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2024/51/</id>
    <title>Awesome Machine Learning Updates on Dec 16 - Dec 22, 2024</title>
    <updated>2024-12-17T02:02:07.204Z</updated>
    <published>2024-12-17T02:02:06.960Z</published>
    <content type="html"><![CDATA[<h3><p>Rust / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/delta-rs/delta" rel="noopener noreferrer">delta (⭐413)</a> - An open source machine learning framework in Rust Δ</li>
</ul>
<h3><p>R / Data Manipulation | Data Analysis | Data Visualization</p>
</h3>
<ul>
<li><a href="https://rdatatable.gitlab.io/data.table/" rel="noopener noreferrer">data.table</a> - <code>data.table</code> provides a high-performance version of base R’s <code>data.frame</code> with syntax and feature enhancements for ease of use, convenience and programming speed.</li>
</ul>
<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/linkedin/isolation-forest" rel="noopener noreferrer">isolation-forest (⭐255)</a> - A distributed Spark/Scala implementation of the isolation forest algorithm for unsupervised outlier detection, featuring support for scalable training and ONNX export for easy cross-platform inference.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/dagworks-inc/hamilton" rel="noopener noreferrer">Hamilton (⭐2.5k)</a> - a lightweight library to define data transformations as a directed-acyclic graph (DAG). It helps author reliable feature engineering and machine learning pipelines, and more.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2024/51/"/>
    <summary>4 awesome projects updated on Dec 16 - Dec 22, 2024</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2024/46/</id>
    <title>Awesome Machine Learning Updates on Nov 11 - Nov 17, 2024</title>
    <updated>2024-11-12T12:50:41.210Z</updated>
    <published>2024-11-12T12:50:40.989Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/comet-ml/opik" rel="noopener noreferrer">Opik (⭐19k)</a>: Evaluate, trace, test, and ship LLM applications across your dev and production lifecycles.</li>
</ul>
<h3><p>Python / Speech Recognition</p>
</h3>
<ul>
<li><a href="https://github.com/espnet/espnet" rel="noopener noreferrer">EspNet (⭐9.8k)</a> - ESPnet is an end-to-end speech processing toolkit for tasks like speech recognition, translation, and enhancement, using PyTorch and Kaldi-style data processing.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2024/46/"/>
    <summary>2 awesome projects updated on Nov 11 - Nov 17, 2024</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2024/32/</id>
    <title>Awesome Machine Learning Updates on Aug 05 - Aug 11, 2024</title>
    <updated>2024-08-08T01:41:32.357Z</updated>
    <published>2024-08-08T01:41:31.258Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/rl-tools/rl-tools" rel="noopener noreferrer">RLtools (⭐968)</a> - The fastest deep reinforcement learning library for continuous control, implemented header-only in pure, dependency-free C++ (Python bindings available as well).</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Okerew/okrolearn" rel="noopener noreferrer">Okrolearn (⭐3)</a>: A python machine learning library created to combine powefull data analasys features with tensors and machine learning components, while maintaining support for other libraries.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2024/32/"/>
    <summary>2 awesome projects updated on Aug 05 - Aug 11, 2024</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2024/24/</id>
    <title>Awesome Machine Learning Updates on Jun 10 - Jun 16, 2024</title>
    <updated>2024-06-11T01:36:37.282Z</updated>
    <published>2024-06-11T01:36:37.282Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://webnn.dev" rel="noopener noreferrer">WebNN</a> - A new web standard that allows web apps and frameworks to accelerate deep neural networks with on-device hardware such as GPUs, CPUs, or purpose-built AI accelerators.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2024/24/"/>
    <summary>1 awesome projects updated on Jun 10 - Jun 16, 2024</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2024/20/</id>
    <title>Awesome Machine Learning Updates on May 13 - May 19, 2024</title>
    <updated>2024-05-19T01:37:25.095Z</updated>
    <published>2024-05-19T01:37:25.095Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://wallaroo.ai/" rel="noopener noreferrer">Wallaroo.AI</a> - Production AI plaftorm for deploying, managing, and observing any model at scale across any environment from cloud to edge. Let's go from python notebook to inferencing in minutes.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2024/20/"/>
    <summary>1 awesome projects updated on May 13 - May 19, 2024</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2024/15/</id>
    <title>Awesome Machine Learning Updates on Apr 08 - Apr 14, 2024</title>
    <updated>2024-04-12T01:22:05.010Z</updated>
    <published>2024-04-09T01:21:51.561Z</published>
    <content type="html"><![CDATA[<h3><p>Go / Reinforcement learning</p>
</h3>
<ul>
<li><a href="https://github.com/DLR-RM/stable-baselines3" rel="noopener noreferrer">stable-baselines3 (⭐13k)</a> - PyTorch implementations of Stable Baselines (deep) reinforcement learning algorithms.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/pyg-team/pytorch-frame" rel="noopener noreferrer">PyTorch Frame (⭐780)</a> -&gt; A Modular Framework for Multi-Modal Tabular Learning.</li>
</ul>

<ul>
<li><a href="https://github.com/pyg-team/pytorch_geometric" rel="noopener noreferrer">PyTorch Geometric (⭐24k)</a> -&gt; Graph Neural Network Library for PyTorch.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2024/15/"/>
    <summary>3 awesome projects updated on Apr 08 - Apr 14, 2024</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2024/14/</id>
    <title>Awesome Machine Learning Updates on Apr 01 - Apr 07, 2024</title>
    <updated>2024-04-01T01:33:33.840Z</updated>
    <published>2024-04-01T01:33:33.840Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/capitalone/datacompy" rel="noopener noreferrer">DataComPy (⭐639)</a> - A library to compare Pandas, Polars, and Spark data frames. It provides stats and lets users adjust for match accuracy.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2024/14/"/>
    <summary>1 awesome projects updated on Apr 01 - Apr 07, 2024</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2024/9/</id>
    <title>Awesome Machine Learning Updates on Feb 26 - Mar 03, 2024</title>
    <updated>2024-02-27T01:19:22.769Z</updated>
    <published>2024-02-27T01:19:22.470Z</published>
    <content type="html"><![CDATA[<h3><p>Rust / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/huggingface/candle" rel="noopener noreferrer">candle (⭐20k)</a> - Candle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use.</li>
</ul>
<h3><p>Rust / Deep Learning</p>
</h3>
<ul>
<li><a href="https://github.com/LaurentMazare/tch-rs" rel="noopener noreferrer">tch-rs (⭐5.4k)</a> - Rust bindings for the C++ API of PyTorch</li>
</ul>

<ul>
<li><a href="https://github.com/coreylowman/dfdx" rel="noopener noreferrer">dfdx (⭐1.9k)</a> - Deep learning in Rust, with shape checked tensors and neural networks</li>
</ul>

<ul>
<li><a href="https://github.com/tracel-ai/burn" rel="noopener noreferrer">burn (⭐15k)</a> - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals</li>
</ul>
<h3><p>Rust / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/huggingface/tokenizers" rel="noopener noreferrer">huggingface/tokenizers (⭐11k)</a> - Fast State-of-the-Art Tokenizers optimized for Research and Production</li>
</ul>

<ul>
<li><a href="https://github.com/guillaume-be/rust-bert" rel="noopener noreferrer">rust-bert (⭐3.1k)</a> - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://www.trychroma.com/" rel="noopener noreferrer">Chroma</a> - Open-source search and retrieval database for AI applications. Vector, full-text, regex, and metadata search. <a href="https://docs.trychroma.com" rel="noopener noreferrer">Self-host</a> or <a href="https://trychroma.com/signup" rel="noopener noreferrer">Cloud</a> available.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2024/9/"/>
    <summary>7 awesome projects updated on Feb 26 - Mar 03, 2024</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2024/4/</id>
    <title>Awesome Machine Learning Updates on Jan 22 - Jan 28, 2024</title>
    <updated>2024-01-25T12:40:19.631Z</updated>
    <published>2024-01-25T12:40:17.983Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://truss.baseten.co" rel="noopener noreferrer">Truss</a> - An open source framework for packaging and serving ML models.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/ml-explore/mlx" rel="noopener noreferrer">MLX (⭐26k)</a>- MLX is an array framework for machine learning on Apple silicon, developed by Apple machine learning research.</li>
</ul>
<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/kinhosz/Neural" rel="noopener noreferrer">Kinho (⭐37)</a> - Simple API for Neural Network. Better for image processing with CPU/GPU + Transfer Learning.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/infiniflow/infinity" rel="noopener noreferrer">Infinity (⭐4.5k)</a> - The AI-native database built for LLM applications, providing incredibly fast vector and full-text search. Developed using C++20</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2024/4/"/>
    <summary>4 awesome projects updated on Jan 22 - Jan 28, 2024</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/49/</id>
    <title>Awesome Machine Learning Updates on Dec 04 - Dec 10, 2023</title>
    <updated>2023-12-07T01:31:47.085Z</updated>
    <published>2023-12-07T01:31:47.085Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/huggingface/transformers" rel="noopener noreferrer">Transformers (⭐159k)</a> - A deep learning library containing thousands of pre-trained models on different tasks. The goto place for anything related to Large Language Models.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/49/"/>
    <summary>1 awesome projects updated on Dec 04 - Dec 10, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/44/</id>
    <title>Awesome Machine Learning Updates on Oct 30 - Nov 05, 2023</title>
    <updated>2023-10-31T01:22:23.394Z</updated>
    <published>2023-10-31T01:22:21.837Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/auto-differentiation/XAD" rel="noopener noreferrer">XAD (⭐412)</a> - Comprehensive backpropagation tool for C++.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/tensorflow/gan" rel="noopener noreferrer">TF-GAN (⭐968)</a> - TF-GAN is a lightweight library for training and evaluating Generative Adversarial Networks (GANs).</li>
</ul>

<ul>
<li><a href="https://github.com/qubvel/segmentation_models.pytorch" rel="noopener noreferrer">segmentation_models.pytorch (⭐12k)</a> - A PyTorch-based toolkit that offers pre-trained segmentation models for computer vision tasks. It simplifies the development of image segmentation applications by providing a collection of popular architecture implementations, such as UNet and PSPNet, along with pre-trained weights, making it easier for researchers and developers to achieve high-quality pixel-level object segmentation in images.</li>
</ul>

<ul>
<li><a href="https://github.com/qubvel/segmentation_models" rel="noopener noreferrer">segmentation_models (⭐4.9k)</a> - A TensorFlow Keras-based toolkit that offers pre-trained segmentation models for computer vision tasks. It simplifies the development of image segmentation applications by providing a collection of popular architecture implementations, such as UNet and PSPNet, along with pre-trained weights, making it easier for researchers and developers to achieve high-quality pixel-level object segmentation in images.</li>
</ul>
<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Farama-Foundation/Gymnasium" rel="noopener noreferrer">Gymnasium (⭐12k)</a> - A library for developing and comparing reinforcement learning algorithms (successor of [gym])(<a href="https://github.com/openai/gym" rel="noopener noreferrer">https://github.com/openai/gym (⭐37k)</a>).</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/44/"/>
    <summary>5 awesome projects updated on Oct 30 - Nov 05, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/37/</id>
    <title>Awesome Machine Learning Updates on Sep 11 - Sep 17, 2023</title>
    <updated>2023-09-12T01:18:29.345Z</updated>
    <published>2023-09-12T01:18:28.916Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/comet-ml/comet-llm" rel="noopener noreferrer">CometLLM (⭐19k)</a> - Track, log, visualize and evaluate your LLM prompts and prompt chains.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/comet-ml/comet-examples" rel="noopener noreferrer">CometML (⭐172)</a>: The best-in-class MLOps platform with experiment tracking, model production monitoring, a model registry, and data lineage from training straight through to production.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/37/"/>
    <summary>2 awesome projects updated on Sep 11 - Sep 17, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/33/</id>
    <title>Awesome Machine Learning Updates on Aug 14 - Aug 20, 2023</title>
    <updated>2023-08-15T01:18:25.868Z</updated>
    <published>2023-08-15T01:18:24.506Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/x-tabdeveloping/neofuzz" rel="noopener noreferrer">Neofuzz (⭐51)</a> - Blazing fast, lightweight and customizable fuzzy and semantic text search in Python with fuzzywuzzy/thefuzz compatible API.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://centre-for-humanities-computing.github.io/tweetopic/" rel="noopener noreferrer">tweetopic</a> - Blazing fast short-text-topic-modelling for Python.</li>
</ul>

<ul>
<li><a href="https://github.com/x-tabdeveloping/topic-wizard" rel="noopener noreferrer">topicwizard (⭐146)</a> - Interactive topic model visualization/interpretation framework.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://synthical.com" rel="noopener noreferrer">Synthical</a> - AI-powered collaborative research environment. You can use it to get recommendations of articles based on reading history, simplify papers, find out what articles are trending, search articles by meaning (not just keywords), create and share folders of articles, see lists of articles from specific companies and universities, and add highlights.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/33/"/>
    <summary>4 awesome projects updated on Aug 14 - Aug 20, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/27/</id>
    <title>Awesome Machine Learning Updates on Jul 03 - Jul 09, 2023</title>
    <updated>2023-07-05T02:02:48.130Z</updated>
    <published>2023-07-05T02:02:47.418Z</published>
    <content type="html"><![CDATA[<h3><p>Go / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/nlpodyssey/cybertron" rel="noopener noreferrer">Cybertron (⭐327)</a> - Cybertron: the home planet of the Transformers in Go.</li>
</ul>
<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/nlpodyssey/spago" rel="noopener noreferrer">Spago (⭐1.8k)</a> - Self-contained Machine Learning and Natural Language Processing library in Go.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/jolibrain/joliGEN" rel="noopener noreferrer">joliGEN (⭐281)</a> - Generative AI Image Toolset with GANs and Diffusion for Real-World Applications.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/27/"/>
    <summary>3 awesome projects updated on Jul 03 - Jul 09, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/25/</id>
    <title>Awesome Machine Learning Updates on Jun 19 - Jun 25, 2023</title>
    <updated>2023-06-21T01:47:30.368Z</updated>
    <published>2023-06-21T01:47:30.368Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/aimhubio/aim" rel="noopener noreferrer">Aim (⭐6.1k)</a> -&gt; An easy-to-use &amp; supercharged open-source AI metadata tracker.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/25/"/>
    <summary>1 awesome projects updated on Jun 19 - Jun 25, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/22/</id>
    <title>Awesome Machine Learning Updates on May 29 - Jun 04, 2023</title>
    <updated>2023-05-31T01:59:00.184Z</updated>
    <published>2023-05-31T01:58:58.302Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://phoenix.arize.com" rel="noopener noreferrer">Phoenix</a> - Uncover insights, surface problems, monitor and fine tune your generative LLM, CV and tabular models.</li>
</ul>
<h3><p>Lua / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/fabprezja/keras-gpt-copilot" rel="noopener noreferrer">Keras GPT Copilot (⭐28)</a> - A python package that integrates an LLM copilot inside the keras model development workflow.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/reactorsh/ambrosia" rel="noopener noreferrer">Ambrosia (⭐113)</a> - Ambrosia helps you clean up your LLM datasets using <em>other</em> LLMs.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/22/"/>
    <summary>3 awesome projects updated on May 29 - Jun 04, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/19/</id>
    <title>Awesome Machine Learning Updates on May 08 - May 14, 2023</title>
    <updated>2023-05-08T01:40:23.656Z</updated>
    <published>2023-05-08T01:40:23.656Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/aqueducthq/aqueduct" rel="noopener noreferrer">Aqueduct (⭐519)</a> - Aqueduct enables you to easily define, run, and manage AI &amp; ML tasks on any cloud infrastructure.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/19/"/>
    <summary>1 awesome projects updated on May 08 - May 14, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/15/</id>
    <title>Awesome Machine Learning Updates on Apr 10 - Apr 16, 2023</title>
    <updated>2023-04-12T01:39:56.023Z</updated>
    <published>2023-04-12T01:39:54.812Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/deepset-ai/haystack" rel="noopener noreferrer">Haystack (⭐25k)</a> - A framework for building industrial-strength applications with Transformer models and LLMs.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/edtechre/pybroker" rel="noopener noreferrer">PyBroker (⭐3.3k)</a> - Algorithmic Trading with Machine Learning.</li>
</ul>

<ul>
<li><a href="https://github.com/IFCA/frouros" rel="noopener noreferrer">Frouros (⭐252)</a>: Frouros is an open source Python library for drift detection in machine learning systems.</li>
</ul>
<h3><p>Books / Misc</p>
</h3>
<ul>
<li><a href="https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1098125975" rel="noopener noreferrer">Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow</a> - Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/15/"/>
    <summary>4 awesome projects updated on Apr 10 - Apr 16, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/9/</id>
    <title>Awesome Machine Learning Updates on Feb 27 - Mar 05, 2023</title>
    <updated>2023-03-04T01:52:22.927Z</updated>
    <published>2023-03-04T01:52:22.927Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://humanloop.com" rel="noopener noreferrer">Humanloop</a> – Humanloop is a platform for prompt experimentation, finetuning models for better performance, cost optimization, and collecting model generated data and user feedback.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/9/"/>
    <summary>1 awesome projects updated on Feb 27 - Mar 05, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/4/</id>
    <title>Awesome Machine Learning Updates on Jan 23 - Jan 29, 2023</title>
    <updated>2023-01-24T01:49:30.819Z</updated>
    <published>2023-01-24T01:49:30.381Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/rwightman/pytorch-image-models" rel="noopener noreferrer">timm (⭐37k)</a> - PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/cleanlab/cleanlab" rel="noopener noreferrer">cleanlab (⭐11k)</a>: The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.</li>
</ul>

<ul>
<li><a href="https://github.com/awslabs/autogluon" rel="noopener noreferrer">AutoGluon (⭐10k)</a>: AutoML for Image, Text, Tabular, Time-Series, and MultiModal Data.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/4/"/>
    <summary>3 awesome projects updated on Jan 23 - Jan 29, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2023/1/</id>
    <title>Awesome Machine Learning Updates on Jan 02 - Jan 08, 2023</title>
    <updated>2023-01-04T01:47:20.933Z</updated>
    <published>2023-01-04T01:47:20.933Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/nebuly-ai/nebullvm/tree/main/apps/accelerate/speedster" rel="noopener noreferrer">Speedster (⭐8.3k)</a> -Automatically apply SOTA optimization techniques to achieve the maximum inference speed-up on your hardware. [DEEP LEARNING]</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2023/1/"/>
    <summary>1 awesome projects updated on Jan 02 - Jan 08, 2023</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/49/</id>
    <title>Awesome Machine Learning Updates on Dec 05 - Dec 11, 2022</title>
    <updated>2022-12-07T01:55:21.698Z</updated>
    <published>2022-12-07T01:55:21.698Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://www.arize.com" rel="noopener noreferrer">Arize AI</a> - Model validation and performance monitoring, drift detection, explainability, visualization across structured and unstructured data</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/49/"/>
    <summary>1 awesome projects updated on Dec 05 - Dec 11, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/47/</id>
    <title>Awesome Machine Learning Updates on Nov 21 - Nov 27, 2022</title>
    <updated>2022-11-24T02:01:34.618Z</updated>
    <published>2022-11-24T02:01:33.415Z</published>
    <content type="html"><![CDATA[<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://tribuo.org" rel="noopener noreferrer">Tribou</a> - A machine learning library written in Java by Oracle.</li>
</ul>
<h3><p>OpenSource-Computer-Vision / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/opencv/opencv" rel="noopener noreferrer">OpenCV (⭐87k)</a> - A OpenSource Computer Vision Library</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://bit.ly/nannyml-github-machinelearning" rel="noopener noreferrer">NannyML</a>: Python library capable of fully capturing the impact of data drift on performance. Allows estimation of post-deployment model performance without access to targets.</li>
</ul>
<h3><p>Python / Spiking Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/synsense/rockpool" rel="noopener noreferrer">Rockpool (⭐81)</a> - A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.</li>
</ul>

<ul>
<li><a href="https://github.com/synsense/sinabs" rel="noopener noreferrer">Sinabs (⭐114)</a> - A deep learning library for spiking neural networks which is based on PyTorch, focuses on fast training and supports inference on neuromorphic hardware.</li>
</ul>

<ul>
<li><a href="https://github.com/neuromorphs/tonic" rel="noopener noreferrer">Tonic (⭐281)</a> - A library that makes downloading publicly available neuromorphic datasets a breeze and provides event-based data transformation/augmentation pipelines.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/47/"/>
    <summary>6 awesome projects updated on Nov 21 - Nov 27, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/45/</id>
    <title>Awesome Machine Learning Updates on Nov 07 - Nov 13, 2022</title>
    <updated>2022-11-07T02:21:33.203Z</updated>
    <published>2022-11-07T02:21:32.111Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/OML-Team/open-metric-learning" rel="noopener noreferrer">OpenMetricLearning (⭐989)</a> - A PyTorch-based framework to train and validate the models producing high-quality embeddings.</li>
</ul>

<ul>
<li><a href="https://github.com/robinthibaut/skbel" rel="noopener noreferrer">SKBEL (⭐26)</a>: A Python library for Bayesian Evidential Learning (BEL) in order to estimate the uncertainty of a prediction.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/matifali/dockerdl" rel="noopener noreferrer">DockerDL (⭐86)</a> - Ready to use deeplearning docker images.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/45/"/>
    <summary>3 awesome projects updated on Nov 07 - Nov 13, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/40/</id>
    <title>Awesome Machine Learning Updates on Oct 03 - Oct 09, 2022</title>
    <updated>2022-10-04T18:55:02.000Z</updated>
    <published>2022-10-04T18:55:02.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/arogozhnikov/einops" rel="noopener noreferrer">einops (⭐9.5k)</a> - Deep learning operations reinvented (for pytorch, tensorflow, jax and others).</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/40/"/>
    <summary>1 awesome projects updated on Oct 03 - Oct 09, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/39/</id>
    <title>Awesome Machine Learning Updates on Sep 26 - Oct 02, 2022</title>
    <updated>2022-09-27T11:25:17.000Z</updated>
    <published>2022-09-27T11:25:17.000Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/neuml/txtai" rel="noopener noreferrer">txtai (⭐12k)</a> - Build semantic search applications and workflows.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/39/"/>
    <summary>1 awesome projects updated on Sep 26 - Oct 02, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/38/</id>
    <title>Awesome Machine Learning Updates on Sep 19 - Sep 25, 2022</title>
    <updated>2022-09-25T15:14:07.000Z</updated>
    <published>2022-09-25T15:14:07.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics" rel="noopener noreferrer">AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics (⭐628)</a>: A tutorial to help machine learning researchers to automatically obtain optimized machine learning models with the optimal learning performance on any specific task.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/38/"/>
    <summary>1 awesome projects updated on Sep 19 - Sep 25, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/36/</id>
    <title>Awesome Machine Learning Updates on Sep 05 - Sep 11, 2022</title>
    <updated>2022-09-09T16:23:28.000Z</updated>
    <published>2022-09-05T14:22:15.000Z</published>
    <content type="html"><![CDATA[<h3><p>TensorFlow / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/markusschanta/awesome-keras" rel="noopener noreferrer">Awesome Keras (⭐32)</a> - A curated list of awesome Keras projects, libraries and resources.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/iterative/mlem" rel="noopener noreferrer">MLEM (⭐717)</a> - Version and deploy your ML models following GitOps principles</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/36/"/>
    <summary>2 awesome projects updated on Sep 05 - Sep 11, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/35/</id>
    <title>Awesome Machine Learning Updates on Aug 29 - Sep 04, 2022</title>
    <updated>2022-08-29T21:13:12.000Z</updated>
    <published>2022-08-29T01:58:45.000Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/instill-ai/vdp" rel="noopener noreferrer">VDP (⭐2.3k)</a> - open source visual data ETL to streamline the end-to-end visual data processing pipeline: extract unstructured visual data from pre-built data sources, transform it into analysable structured insights by Vision AI models imported from various ML platforms, and load the insights into warehouses or applications.</li>
</ul>

<ul>
<li><a href="https://www.comet.com/" rel="noopener noreferrer">Comet</a> -  ML platform for tracking experiments, hyper-parameters, artifacts and more. It's deeply integrated with over 15+ deep learning frameworks and orchestration tools. Users can also use the platform to monitor their models in production.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/35/"/>
    <summary>2 awesome projects updated on Aug 29 - Sep 04, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/31/</id>
    <title>Awesome Machine Learning Updates on Aug 01 - Aug 07, 2022</title>
    <updated>2022-08-07T18:39:32.000Z</updated>
    <published>2022-08-07T18:39:32.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/cicirello/Chips-n-Salsa" rel="noopener noreferrer">Chips-n-Salsa (⭐74)</a> - A Java library for genetic algorithms, evolutionary computation, and stochastic local search, with a focus on self-adaptation / self-tuning, as well as parallel execution.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/31/"/>
    <summary>1 awesome projects updated on Aug 01 - Aug 07, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/28/</id>
    <title>Awesome Machine Learning Updates on Jul 11 - Jul 17, 2022</title>
    <updated>2022-07-17T13:43:53.000Z</updated>
    <published>2022-07-14T09:12:30.000Z</published>
    <content type="html"><![CDATA[<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/nikolaydubina/go-ml-benchmarks" rel="noopener noreferrer">go-ml-benchmarks (⭐32)</a> — benchmarks of machine learning inference for Go.</li>
</ul>
<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/encog/encog-java-core" rel="noopener noreferrer">Encog (⭐752)</a> - An advanced neural network and machine learning framework. Encog contains classes to create a wide variety of networks, as well as support classes to normalize and process data for these neural networks. Encog trainings using multithreaded resilient propagation. Encog can also make use of a GPU to further speed processing time. A GUI based workbench is also provided to help model and train neural networks.</li>
</ul>

<ul>
<li><a href="http://neuroph.sourceforge.net/" rel="noopener noreferrer">Neuroph</a> - Neuroph is lightweight Java neural network framework.</li>
</ul>
<h3><p>Java / Deep Learning</p>
</h3>
<ul>
<li><a href="https://victorzhou.com/blog/keras-neural-network-tutorial/" rel="noopener noreferrer">Keras Beginner Tutorial</a> - Friendly guide on using Keras to implement a simple Neural Network in Python.</li>
</ul>
<h3><p>JavaScript / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/axa-group/nlp.js" rel="noopener noreferrer">nlp.js (⭐6.6k)</a> - An NLP library built in node over Natural, with entity extraction, sentiment analysis, automatic language identify, and so more.</li>
</ul>
<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Hoff97/tensorjs" rel="noopener noreferrer">tensor-js (⭐38)</a> - A deep learning library for the browser, accelerated by WebGL and WebAssembly.</li>
</ul>
<h3><p>Julia / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/alan-turing-institute/MLJ.jl" rel="noopener noreferrer">MLJ (⭐1.9k)</a> - A Julia machine learning framework.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/upgini/upgini" rel="noopener noreferrer">Upgini (⭐347)</a>: Free automated data &amp; feature enrichment library for machine learning - automatically searches through thousands of ready-to-use features from public and community shared data sources and enriches your training dataset with only the accuracy improving features.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/28/"/>
    <summary>8 awesome projects updated on Jul 11 - Jul 17, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/24/</id>
    <title>Awesome Machine Learning Updates on Jun 13 - Jun 19, 2022</title>
    <updated>2022-06-16T19:25:33.000Z</updated>
    <published>2022-06-16T19:25:33.000Z</published>
    <content type="html"><![CDATA[<h3><p>Clojure / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/scicloj/scicloj.ml" rel="noopener noreferrer">scicloj.ml (⭐238)</a> -  A idiomatic Clojure machine learning library based on tech.ml.dataset with a unique approach for immutable data processing pipelines.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/24/"/>
    <summary>1 awesome projects updated on Jun 13 - Jun 19, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/21/</id>
    <title>Awesome Machine Learning Updates on May 23 - May 29, 2022</title>
    <updated>2022-05-24T14:50:27.000Z</updated>
    <published>2022-05-24T02:28:25.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/MAIF/shapash" rel="noopener noreferrer">Shapash (⭐3.2k)</a> : Shapash is a Python library that provides several types of visualization that display explicit labels that everyone can understand.</li>
</ul>

<ul>
<li><a href="https://github.com/MAIF/eurybia" rel="noopener noreferrer">Eurybia (⭐218)</a>: Eurybia monitors data and model drift over time and securizes model deployment with data validation.</li>
</ul>

<ul>
<li><a href="https://github.com/hpcaitech/ColossalAI" rel="noopener noreferrer">Colossal-AI (⭐41k)</a>: An open-source deep learning system for large-scale model training and inference with high efficiency and low cost.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/21/"/>
    <summary>3 awesome projects updated on May 23 - May 29, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/20/</id>
    <title>Awesome Machine Learning Updates on May 16 - May 22, 2022</title>
    <updated>2022-05-19T06:18:47.000Z</updated>
    <published>2022-05-18T12:20:18.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/CEA-LIST/N2D2" rel="noopener noreferrer">N2D2 (⭐158)</a> - CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://qdrant.tech" rel="noopener noreferrer">Qdrant</a> – Qdrant is <a href="https://github.com/qdrant/qdrant" rel="noopener noreferrer">open source (⭐30k)</a> vector similarity search engine with extended filtering support, written in Rust.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/20/"/>
    <summary>2 awesome projects updated on May 16 - May 22, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/18/</id>
    <title>Awesome Machine Learning Updates on May 02 - May 08, 2022</title>
    <updated>2022-05-05T21:54:34.000Z</updated>
    <published>2022-05-05T21:54:34.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/oneapi-src/oneDNN" rel="noopener noreferrer">oneDNN (⭐4k)</a> - An open-source cross-platform performance library for deep learning applications.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/18/"/>
    <summary>1 awesome projects updated on May 02 - May 08, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/15/</id>
    <title>Awesome Machine Learning Updates on Apr 11 - Apr 17, 2022</title>
    <updated>2022-04-14T03:34:09.000Z</updated>
    <published>2022-04-14T03:34:09.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/opendilab/DI-engine" rel="noopener noreferrer">DI-engine (⭐3.6k)</a> - DI-engine is a generalized Decision Intelligence engine. It supports most basic deep reinforcement learning (DRL) algorithms, such as DQN, PPO, SAC, and domain-specific algorithms like QMIX in multi-agent RL, GAIL in inverse RL, and RND in exploration problems.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://milvus.io" rel="noopener noreferrer">milvus</a> – Milvus is <a href="https://github.com/milvus-io/milvus" rel="noopener noreferrer">open source (⭐44k)</a> vector database for production AI, written in Go and C++, scalable and blazing fast for billions of embedding vectors.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/15/"/>
    <summary>2 awesome projects updated on Apr 11 - Apr 17, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/14/</id>
    <title>Awesome Machine Learning Updates on Apr 04 - Apr 10, 2022</title>
    <updated>2022-04-08T23:14:17.000Z</updated>
    <published>2022-04-08T23:03:03.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Python Survival Analysis</p>
</h3>
<ul>
<li><a href="https://github.com/CamDavidsonPilon/lifelines" rel="noopener noreferrer">lifelines (⭐2.6k)</a> - lifelines is a complete survival analysis library, written in pure Python</li>
</ul>

<ul>
<li><a href="https://github.com/sebp/scikit-survival" rel="noopener noreferrer">Scikit-Survival (⭐1.3k)</a> - scikit-survival is a Python module for survival analysis built on top of scikit-learn. It allows doing survival analysis while utilizing the power of scikit-learn, e.g., for pre-processing or doing cross-validation.</li>
</ul>
<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://cran.r-project.org/web/packages/CORElearn/index.html" rel="noopener noreferrer">CORElearn</a> - CORElearn: Classification, regression, feature evaluation and ordinal evaluation.
-* <a href="https://cran.r-project.org/web/packages/CoxBoost/index.html" rel="noopener noreferrer">CoxBoost</a> - CoxBoost: Cox models by likelihood based boosting for a single survival endpoint or competing risks <strong>[Deprecated]</strong></li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/14/"/>
    <summary>3 awesome projects updated on Apr 04 - Apr 10, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/12/</id>
    <title>Awesome Machine Learning Updates on Mar 21 - Mar 27, 2022</title>
    <updated>2022-03-24T09:19:56.000Z</updated>
    <published>2022-03-24T09:19:56.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://towhee.io" rel="noopener noreferrer">Towhee</a> - A Python module that encode unstructured data into embeddings.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/12/"/>
    <summary>1 awesome projects updated on Mar 21 - Mar 27, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/11/</id>
    <title>Awesome Machine Learning Updates on Mar 14 - Mar 20, 2022</title>
    <updated>2022-03-18T13:31:30.000Z</updated>
    <published>2022-03-18T13:31:30.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Federated Learning</p>
</h3>
<ul>
<li><a href="https://github.com/OpenMined/PySyft" rel="noopener noreferrer">PySyft (⭐9.9k)</a> - A Python library for secure and private Deep Learning.</li>
</ul>

<ul>
<li><a href="https://flower.dev/" rel="noopener noreferrer">Flower</a> - A unified approach to federated learning, analytics, and evaluation. Federate any workload, any ML framework, and any programming language.</li>
</ul>

<ul>
<li><a href="https://www.tensorflow.org/federated" rel="noopener noreferrer">Tensorflow-Federated</a> A federated learning framework for machine learning and other computations on decentralized data.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/11/"/>
    <summary>3 awesome projects updated on Mar 14 - Mar 20, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/10/</id>
    <title>Awesome Machine Learning Updates on Mar 07 - Mar 13, 2022</title>
    <updated>2022-03-10T10:13:21.000Z</updated>
    <published>2022-03-10T10:13:21.000Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/chaos-genius/chaos_genius/" rel="noopener noreferrer">Chaos Genius (⭐777)</a> - ML powered analytics engine for outlier/anomaly detection and root cause analysis.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/10/"/>
    <summary>1 awesome projects updated on Mar 07 - Mar 13, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/5/</id>
    <title>Awesome Machine Learning Updates on Jan 31 - Feb 06, 2022</title>
    <updated>2022-01-31T13:52:17.000Z</updated>
    <published>2022-01-31T13:52:17.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/serengil/deepface" rel="noopener noreferrer">deepface (⭐23k)</a> - A lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for Python covering cutting-edge models such as VGG-Face, FaceNet, OpenFace, DeepFace, DeepID, Dlib and ArcFace.</li>
</ul>

<ul>
<li><a href="https://github.com/serengil/retinaface" rel="noopener noreferrer">retinaface (⭐2k)</a> - deep learning based cutting-edge facial detector for Python coming with facial landmarks</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/serengil/chefboost" rel="noopener noreferrer">ChefBoost (⭐486)</a> - a lightweight decision tree framework for Python with categorical feature support covering regular decision tree algorithms such as ID3, C4.5, CART, CHAID and regression tree; also some advanced bagging and boosting techniques such as gradient boosting, random forest and adaboost.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/5/"/>
    <summary>3 awesome projects updated on Jan 31 - Feb 06, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/2/</id>
    <title>Awesome Machine Learning Updates on Jan 10 - Jan 16, 2022</title>
    <updated>2022-01-11T00:30:34.000Z</updated>
    <published>2022-01-11T00:30:34.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/wannesm/dtaidistance" rel="noopener noreferrer">dtaidistance (⭐1.2k)</a> - High performance library for time series distances (DTW) and time series clustering.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/ageron/handson-ml" rel="noopener noreferrer">handsonml (⭐26k)</a> - Fundamentals of machine learning in python.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/2/"/>
    <summary>2 awesome projects updated on Jan 10 - Jan 16, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2022/1/</id>
    <title>Awesome Machine Learning Updates on Jan 03 - Jan 09, 2022</title>
    <updated>2022-01-08T14:07:29.000Z</updated>
    <published>2022-01-08T14:07:29.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/vaexio/vaex" rel="noopener noreferrer">Vaex (⭐8.5k)</a> - A high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets. Documentation can be found <a href="https://vaex.io/docs/index.html" rel="noopener noreferrer">here</a>.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2022/1/"/>
    <summary>1 awesome projects updated on Jan 03 - Jan 09, 2022</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/52/</id>
    <title>Awesome Machine Learning Updates on Dec 27 - Jan 02, 2021</title>
    <updated>2021-12-30T18:41:04.000Z</updated>
    <published>2021-12-29T14:35:33.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/AstraZeneca/rexmex" rel="noopener noreferrer">RexMex (⭐277)</a> -&gt; A general purpose recommender metrics library for fair evaluation.</li>
</ul>

<ul>
<li><a href="https://github.com/AstraZeneca/chemicalx" rel="noopener noreferrer">ChemicalX (⭐776)</a> -&gt; A PyTorch based deep learning library for drug pair scoring</li>
</ul>

<ul>
<li><a href="https://github.com/deepchecks/deepchecks" rel="noopener noreferrer">Deepchecks (⭐4k)</a>: Validation &amp; testing of machine learning models and data during model development, deployment, and production. This includes checks and suites related to various types of issues, such as model performance, data integrity, distribution mismatches, and more.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/52/"/>
    <summary>3 awesome projects updated on Dec 27 - Jan 02, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/51/</id>
    <title>Awesome Machine Learning Updates on Dec 20 - Dec 26, 2021</title>
    <updated>2021-12-22T19:35:35.000Z</updated>
    <published>2021-12-21T18:17:17.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/ClimbsRocks/auto_ml" rel="noopener noreferrer">Auto ML (⭐1.7k)</a> - Automated machine learning, data formatting, ensembling, and hyperparameter optimization for competitions and exploration- just give it a .csv file! <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/nicohlr/ipychart" rel="noopener noreferrer">ipychart (⭐131)</a> - The power of Chart.js in Jupyter Notebook.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/51/"/>
    <summary>2 awesome projects updated on Dec 20 - Dec 26, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/50/</id>
    <title>Awesome Machine Learning Updates on Dec 13 - Dec 19, 2021</title>
    <updated>2021-12-17T22:07:08.000Z</updated>
    <published>2021-12-17T22:07:08.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/pycaret/pycaret" rel="noopener noreferrer">PyCaret (⭐9.7k)</a> - An open-source, low-code machine learning library in Python that automates machine learning workflows.</li>
</ul>
<h3><p>Clojure / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/joshuaeckroth/clj-ml/" rel="noopener noreferrer">clj-ml (⭐134)</a> - A machine learning library for Clojure built on top of Weka and friends.</li>
</ul>

<ul>
<li><a href="https://github.com/ptaoussanis/touchstone" rel="noopener noreferrer">Touchstone (⭐139)</a> - Clojure A/B testing library.</li>
</ul>
<h3><p>Clojure / Deep Learning</p>
</h3>
<ul>
<li><a href="https://github.com/aria42/flare" rel="noopener noreferrer">Flare (⭐287)</a> - Dynamic Tensor Graph library in Clojure (think PyTorch, DynNet, etc.)</li>
</ul>
<h3><p>Clojure / Data Analysis</p>
</h3>
<ul>
<li><a href="https://github.com/techascent/tech.ml.dataset" rel="noopener noreferrer">tech.ml.dataset (⭐743)</a> - Clojure dataframe library and pipeline for data processing and machine learning</li>
</ul>
<h3><p>Clojure / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/pink-gorilla/gorilla-notebook" rel="noopener noreferrer">Pink Gorilla Notebook (⭐107)</a> - A Clojure/Clojurescript notebook application/-library based on Gorilla-REPL</li>
</ul>

<ul>
<li><a href="https://github.com/scicloj/notespace" rel="noopener noreferrer">notespace (⭐149)</a> - Notebook experience in your Clojure namespace</li>
</ul>

<ul>
<li><a href="https://github.com/datamechanics/delight" rel="noopener noreferrer">Delight (⭐346)</a> - A listener that streams your spark events logs to delight, a free and improved spark UI</li>
</ul>
<h3><p>Clojure / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/MastodonC/kixi.stats" rel="noopener noreferrer">kixistats (⭐368)</a> - A library of statistical distribution sampling and transducing functions</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/facebookresearch/detectron2" rel="noopener noreferrer">detectron2 (⭐34k)</a> - FAIR's next-generation research platform for object detection and segmentation. It is a ground-up rewrite of the previous version, Detectron, and is powered by the PyTorch deep learning framework.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/benedekrozemberczki/shapley" rel="noopener noreferrer">Shapley (⭐225)</a> -&gt; A data-driven framework to quantify the value of classifiers in a machine learning ensemble.</li>
</ul>

<ul>
<li><a href="https://github.com/breze-no-salt/breze" rel="noopener noreferrer">breze (⭐95)</a> - Theano based library for deep and recurrent neural networks.</li>
</ul>

<ul>
<li><a href="https://github.com/gugarosa/opytimizer" rel="noopener noreferrer">Opytimizer (⭐632)</a> - Python-based meta-heuristic optimization techniques.</li>
</ul>
<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/mrT23/TResNet" rel="noopener noreferrer">TResNet: High Performance GPU-Dedicated Architecture (⭐478)</a> - TResNet models were designed and optimized to give the best speed-accuracy tradeoff out there on GPUs.</li>
</ul>

<ul>
<li><a href="https://jina.ai/" rel="noopener noreferrer">Jina AI</a> An easier way to build neural search in the cloud. Compatible with Jupyter Notebooks.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://flyte.org/" rel="noopener noreferrer">Flyte</a> - Flyte makes it easy to create concurrent, scalable, and maintainable workflows for machine learning and data processing.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/50/"/>
    <summary>16 awesome projects updated on Dec 13 - Dec 19, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/49/</id>
    <title>Awesome Machine Learning Updates on Dec 06 - Dec 12, 2021</title>
    <updated>2021-12-07T10:31:25.000Z</updated>
    <published>2021-12-06T12:45:16.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / Deep Learning</p>
</h3>
<ul>
<li><a href="https://github.com/deepjavalibrary/djl" rel="noopener noreferrer">deepjavalibrary/djl (⭐4.8k)</a> - Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning, designed to be easy to get started with and simple to use for Java developers.</li>
</ul>
<h3><p>Kotlin / Deep Learning</p>
</h3>
<ul>
<li><a href="https://github.com/JetBrains/KotlinDL" rel="noopener noreferrer">KotlinDL (⭐1.6k)</a> - Deep learning framework written in Kotlin.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/49/"/>
    <summary>2 awesome projects updated on Dec 06 - Dec 12, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/48/</id>
    <title>Awesome Machine Learning Updates on Nov 29 - Dec 05, 2021</title>
    <updated>2021-11-29T10:45:09.000Z</updated>
    <published>2021-11-29T10:45:09.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/ZhiningLiu1998/imbalanced-ensemble" rel="noopener noreferrer">imbalanced-ensemble (⭐423)</a> - Python toolbox for quick implementation, modification, evaluation, and visualization of ensemble learning algorithms for class-imbalanced data. Supports out-of-the-box multi-class imbalanced (long-tailed) classification.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/48/"/>
    <summary>1 awesome projects updated on Nov 29 - Dec 05, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/47/</id>
    <title>Awesome Machine Learning Updates on Nov 22 - Nov 28, 2021</title>
    <updated>2021-11-23T03:31:34.000Z</updated>
    <published>2021-11-23T03:31:34.000Z</published>
    <content type="html"><![CDATA[<h3><p>Books / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/terrytangyuan/distributed-ml-patterns" rel="noopener noreferrer">Distributed Machine Learning Patterns (⭐501)</a>  - This book teaches you how to take machine learning models from your personal laptop to large distributed clusters. You’ll explore key concepts and patterns behind successful distributed machine learning systems, and learn technologies like TensorFlow, Kubernetes, Kubeflow, and Argo Workflows directly from a key maintainer and contributor, with real-world scenarios and hands-on projects.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/47/"/>
    <summary>1 awesome projects updated on Nov 22 - Nov 28, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/44/</id>
    <title>Awesome Machine Learning Updates on Nov 01 - Nov 07, 2021</title>
    <updated>2021-11-04T22:11:26.000Z</updated>
    <published>2021-11-04T22:11:26.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/keras-team/keras-tuner" rel="noopener noreferrer">Keras Tuner (⭐2.9k)</a> - An easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/44/"/>
    <summary>1 awesome projects updated on Nov 01 - Nov 07, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/42/</id>
    <title>Awesome Machine Learning Updates on Oct 18 - Oct 24, 2021</title>
    <updated>2021-10-19T20:27:27.000Z</updated>
    <published>2021-10-19T20:27:27.000Z</published>
    <content type="html"><![CDATA[<h3><p>Rust / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/smartcorelib/smartcore" rel="noopener noreferrer">smartcore (⭐904)</a> - "The Most Advanced Machine Learning Library In Rust."</li>
</ul>

<ul>
<li><a href="https://github.com/rust-ml/linfa" rel="noopener noreferrer">linfa (⭐4.6k)</a> - <code>linfa</code> aims to provide a comprehensive toolkit to build Machine Learning applications with Rust</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/42/"/>
    <summary>2 awesome projects updated on Oct 18 - Oct 24, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/40/</id>
    <title>Awesome Machine Learning Updates on Oct 04 - Oct 10, 2021</title>
    <updated>2021-10-04T14:55:53.000Z</updated>
    <published>2021-10-04T14:55:53.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/natanielruiz/dockerface" rel="noopener noreferrer">dockerface (⭐191)</a> - Easy to install and use deep learning Faster R-CNN face detection for images and video in a docker container. <strong>[Deprecated]</strong></li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/40/"/>
    <summary>1 awesome projects updated on Oct 04 - Oct 10, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/39/</id>
    <title>Awesome Machine Learning Updates on Sep 27 - Oct 03, 2021</title>
    <updated>2021-10-03T03:03:29.000Z</updated>
    <published>2021-09-27T15:01:13.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/exadel-inc/CompreFace" rel="noopener noreferrer">Exadel CompreFace (⭐7.9k)</a> - face recognition system that can be easily integrated into any system without prior machine learning skills. CompreFace provides REST API for face recognition, face verification, face detection, face mask detection, landmark detection, age, and gender recognition and is easily deployed with docker.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/streamlit/streamlit" rel="noopener noreferrer">Streamlit (⭐44k)</a>: Streamlit is an framework to create beautiful data apps in hours, not weeks.</li>
</ul>

<ul>
<li><a href="https://github.com/optuna/optuna" rel="noopener noreferrer">Optuna (⭐14k)</a>: Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/ShivamChoudhary17/Heart_Disease" rel="noopener noreferrer">Heart_Disease-Prediction (⭐1)</a> - Given clinical parameters about a patient, can we predict whether or not they have heart disease?</li>
</ul>

<ul>
<li><a href="https://github.com/ShivamChoudhary17/Flight_Fare_Prediction" rel="noopener noreferrer">Flight Fare Prediction (⭐1)</a> - This basically to gauge the understanding of Machine Learning Workflow and Regression technique in specific.</li>
</ul>
<h3><p>Books / Misc</p>
</h3>
<ul>
<li><a href="https://netron.app/" rel="noopener noreferrer">Netron</a> - An opensource viewer for neural network, deep learning and machine learning models</li>
</ul>

<ul>
<li><a href="https://teachablemachine.withgoogle.com/" rel="noopener noreferrer">Teachable Machine</a> - Train Machine Learning models on the fly to recognize your own images, sounds, &amp; poses.</li>
</ul>

<ul>
<li><a href="https://modelzoo.co/" rel="noopener noreferrer">Model Zoo</a> - Discover open source deep learning code and pretrained models.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/39/"/>
    <summary>8 awesome projects updated on Sep 27 - Oct 03, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/38/</id>
    <title>Awesome Machine Learning Updates on Sep 20 - Sep 26, 2021</title>
    <updated>2021-09-22T13:35:13.000Z</updated>
    <published>2021-09-22T13:35:13.000Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/iterative/dvclive" rel="noopener noreferrer">DVClive (⭐189)</a> - Python library for experiment metrics logging into simply formatted local files.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/38/"/>
    <summary>1 awesome projects updated on Sep 20 - Sep 26, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/36/</id>
    <title>Awesome Machine Learning Updates on Sep 06 - Sep 12, 2021</title>
    <updated>2021-09-09T13:27:46.000Z</updated>
    <published>2021-09-07T13:06:30.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/Charmve/computer-vision-in-action" rel="noopener noreferrer">computer-vision-in-action (⭐2.8k)</a> - as known as <code>L0CV</code>, is a new generation of computer vision open source online learning media, a cross-platform interactive learning framework integrating graphics, source code and HTML. the L0CV ecosystem — Notebook, Datasets, Source Code, and from Diving-in to Advanced — as well as the L0CV Hub.</li>
</ul>
<h3><p>Books / Misc</p>
</h3>
<ul>
<li><a href="https://www.manning.com/books/grokking-machine-learning" rel="noopener noreferrer">Grokking Machine Learning</a> - Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math.</li>
</ul>

<ul>
<li><a href="https://www.manning.com/books/machine-learning-bookcamp" rel="noopener noreferrer">Machine Learning Bookcamp</a> - Learn the essentials of machine learning by completing a carefully designed set of real-world projects.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/36/"/>
    <summary>3 awesome projects updated on Sep 06 - Sep 12, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/35/</id>
    <title>Awesome Machine Learning Updates on Aug 30 - Sep 05, 2021</title>
    <updated>2021-09-04T14:19:29.000Z</updated>
    <published>2021-09-02T08:43:10.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.ee.ucl.ac.uk/~mflanaga/java/" rel="noopener noreferrer">Dr. Michael Thomas Flanagan's Java Scientific Library.</a> <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li>More tools to improve the ML lifecycle: <a href="https://github.com/catalyst-team/catalyst" rel="noopener noreferrer">Catalyst (⭐3.4k)</a>, <a href="https://www.pachyderm.io/" rel="noopener noreferrer">PachydermIO</a>. The following are GitHub-alike and targeting teams <a href="https://www.wandb.com/" rel="noopener noreferrer">Weights &amp; Biases</a>, <a href="https://neptune.ai/" rel="noopener noreferrer">Neptune.ai</a>, <a href="https://www.comet.ml/" rel="noopener noreferrer">Comet.ml</a>, <a href="https://valohai.com/" rel="noopener noreferrer">Valohai.ai</a>, <a href="https://DAGsHub.com/" rel="noopener noreferrer">DAGsHub</a>.</li>
</ul>

<ul>
<li><a href="https://www.semi.technology/developers/weaviate/current/" rel="noopener noreferrer">Weaviate</a> – Weaviate is an <a href="https://github.com/semi-technologies/weaviate" rel="noopener noreferrer">open source (⭐16k)</a> vector search engine and vector database. Weaviate uses machine learning to vectorize and store data, and to find answers to natural language queries. With Weaviate you can also bring your custom ML models to production scale.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/35/"/>
    <summary>3 awesome projects updated on Aug 30 - Sep 05, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/34/</id>
    <title>Awesome Machine Learning Updates on Aug 23 - Aug 29, 2021</title>
    <updated>2021-08-25T07:06:52.000Z</updated>
    <published>2021-08-25T07:06:52.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/ray-project/ray" rel="noopener noreferrer">RLlib (⭐42k)</a> - RLlib is an industry level, highly scalable RL library for tf and torch, based on Ray. It's used by companies like Amazon and Microsoft to solve real-world decision making problems at scale.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/34/"/>
    <summary>1 awesome projects updated on Aug 23 - Aug 29, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/30/</id>
    <title>Awesome Machine Learning Updates on Jul 26 - Aug 01, 2021</title>
    <updated>2021-07-29T13:18:24.000Z</updated>
    <published>2021-07-29T13:18:24.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/Ret2Me/IoT-Owl" rel="noopener noreferrer">IoT Owl (⭐9)</a> - Light face detection and recognition system with huge possibilities, based on Microsoft Face API and TensorFlow made for small IoT devices like raspberry pi.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/30/"/>
    <summary>1 awesome projects updated on Jul 26 - Aug 01, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/27/</id>
    <title>Awesome Machine Learning Updates on Jul 05 - Jul 11, 2021</title>
    <updated>2021-07-05T14:58:11.000Z</updated>
    <published>2021-07-05T14:58:11.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/intel/scikit-learn-intelex" rel="noopener noreferrer">Intel(R) Extension for Scikit-learn (⭐1.3k)</a> - A seamless way to speed up your Scikit-learn applications with no accuracy loss and code changes.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/27/"/>
    <summary>1 awesome projects updated on Jul 05 - Jul 11, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/26/</id>
    <title>Awesome Machine Learning Updates on Jun 28 - Jul 04, 2021</title>
    <updated>2021-06-30T18:59:37.000Z</updated>
    <published>2021-06-30T12:31:09.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/oneapi-src/oneDAL" rel="noopener noreferrer">Intel® oneAPI Data Analytics Library (⭐645)</a> - A high performance software library developed by Intel and optimized for Intel's architectures. Library provides algorithmic building blocks for all stages of data analytics and allows to process data in batch, online and distributed modes.</li>
</ul>
<h3><p>JavaScript / Demos and Scripts</p>
</h3>
<ul>
<li><a href="https://heroeswearmasks.fun/" rel="noopener noreferrer">Heroes Wear Masks</a> - A fun TensorFlow.js-based oracle that tells, whether one wears a face mask or not. It can even tell when one wears the mask incorrectly.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/26/"/>
    <summary>2 awesome projects updated on Jun 28 - Jul 04, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/25/</id>
    <title>Awesome Machine Learning Updates on Jun 21 - Jun 27, 2021</title>
    <updated>2021-06-27T18:21:12.000Z</updated>
    <published>2021-06-27T18:21:12.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/rodrigo-arenas/Sklearn-genetic-opt" rel="noopener noreferrer">Sklearn-genetic-opt (⭐360)</a>: An AutoML package for hyperparameters tuning using evolutionary algorithms, with built-in callbacks, plotting, remote logging and more.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/25/"/>
    <summary>1 awesome projects updated on Jun 21 - Jun 27, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/24/</id>
    <title>Awesome Machine Learning Updates on Jun 14 - Jun 20, 2021</title>
    <updated>2021-06-18T08:55:12.000Z</updated>
    <published>2021-06-18T08:55:12.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/evidentlyai/evidently" rel="noopener noreferrer">Evidently (⭐7.4k)</a>: Interactive reports to analyze machine learning models during validation or production monitoring.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/24/"/>
    <summary>1 awesome projects updated on Jun 14 - Jun 20, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/22/</id>
    <title>Awesome Machine Learning Updates on May 31 - Jun 06, 2021</title>
    <updated>2021-06-05T18:10:04.000Z</updated>
    <published>2021-06-01T14:30:08.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/nccr-itmo/FEDOT" rel="noopener noreferrer">FEDOT (⭐704)</a>: An AutoML framework for the automated design of composite modelling pipelines. It can handle classification, regression, and time series forecasting tasks on different types of data (including multi-modal datasets).</li>
</ul>
<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/enlite-ai/maze" rel="noopener noreferrer">Maze (⭐286)</a> - Application-oriented deep reinforcement learning framework addressing real-world decision problems.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/22/"/>
    <summary>2 awesome projects updated on May 31 - Jun 06, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/21/</id>
    <title>Awesome Machine Learning Updates on May 24 - May 30, 2021</title>
    <updated>2021-05-24T16:31:06.000Z</updated>
    <published>2021-05-24T16:31:06.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/openvisionapi" rel="noopener noreferrer">OpenVisionAPI</a> - Open source computer vision API based on open source models.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/21/"/>
    <summary>1 awesome projects updated on May 24 - May 30, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/16/</id>
    <title>Awesome Machine Learning Updates on Apr 19 - Apr 25, 2021</title>
    <updated>2021-04-23T12:09:45.000Z</updated>
    <published>2021-04-22T15:35:48.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/felipexw/knn-java-library" rel="noopener noreferrer">knn-java-library (⭐7)</a> - Just a simple implementation of K-Nearest Neighbors algorithm using with a bunch of similarity measures.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://about.mlreef.com/" rel="noopener noreferrer">MLReef</a> - MLReef is an end-to-end development platform using the power of git to give structure and deep collaboration possibilities to the ML development process.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/16/"/>
    <summary>2 awesome projects updated on Apr 19 - Apr 25, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/15/</id>
    <title>Awesome Machine Learning Updates on Apr 12 - Apr 18, 2021</title>
    <updated>2021-04-15T12:05:53.000Z</updated>
    <published>2021-04-13T16:54:42.000Z</published>
    <content type="html"><![CDATA[<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Azure/mmlspark" rel="noopener noreferrer">Microsoft ML for Apache Spark (⭐5.2k)</a> -&gt; A distributed machine learning framework Apache Spark</li>
</ul>

<ul>
<li><a href="https://github.com/EmergentOrder/onnx-scala" rel="noopener noreferrer">ONNX-Scala (⭐146)</a> - An ONNX (Open Neural Network eXchange) API and backend for typeful, functional deep learning in Scala (3).</li>
</ul>
<h3><p>Scala / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/SciScala/NDScala" rel="noopener noreferrer">NDScala (⭐48)</a> - N-dimensional arrays in Scala 3. Think NumPy ndarray, but with compile-time type-checking/inference over shapes, tensor/axis labels &amp; numeric data types</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/15/"/>
    <summary>3 awesome projects updated on Apr 12 - Apr 18, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/12/</id>
    <title>Awesome Machine Learning Updates on Mar 22 - Mar 28, 2021</title>
    <updated>2021-03-23T20:33:59.000Z</updated>
    <published>2021-03-23T20:33:59.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/backprop-ai/backprop" rel="noopener noreferrer">Backprop (⭐241)</a> - Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/12/"/>
    <summary>1 awesome projects updated on Mar 22 - Mar 28, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/11/</id>
    <title>Awesome Machine Learning Updates on Mar 15 - Mar 21, 2021</title>
    <updated>2021-03-21T17:12:22.000Z</updated>
    <published>2021-03-21T17:12:22.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/xhlulu/dl-translate" rel="noopener noreferrer">DL Translate (⭐498)</a> - A deep learning-based translation library between 50 languages, built with <code>transformers</code>.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/11/"/>
    <summary>1 awesome projects updated on Mar 15 - Mar 21, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/10/</id>
    <title>Awesome Machine Learning Updates on Mar 08 - Mar 14, 2021</title>
    <updated>2021-03-10T09:09:32.000Z</updated>
    <published>2021-03-09T10:28:05.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://questdb.io/" rel="noopener noreferrer">QuestDB</a> - A relational column-oriented database designed for real-time analytics on time series and event data.</li>
</ul>
<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/mil-tokyo/webdnn" rel="noopener noreferrer">WebDNN (⭐2k)</a> - Fast Deep Neural Network JavaScript Framework. WebDNN uses next generation JavaScript API, WebGPU for GPU execution, and WebAssembly for CPU execution.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/online-ml/river" rel="noopener noreferrer">River (⭐5.8k)</a>: A framework for general purpose online machine learning.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/10/"/>
    <summary>3 awesome projects updated on Mar 08 - Mar 14, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/8/</id>
    <title>Awesome Machine Learning Updates on Feb 22 - Feb 28, 2021</title>
    <updated>2021-02-28T17:13:42.000Z</updated>
    <published>2021-02-28T17:13:42.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/bytehub-ai/bytehub" rel="noopener noreferrer">ByteHub (⭐61)</a> - An easy-to-use, Python-based feature store. Optimized for time-series data.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/8/"/>
    <summary>1 awesome projects updated on Feb 22 - Feb 28, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/6/</id>
    <title>Awesome Machine Learning Updates on Feb 08 - Feb 14, 2021</title>
    <updated>2021-02-10T08:41:43.000Z</updated>
    <published>2021-02-10T08:41:43.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/activeloopai/Hub" rel="noopener noreferrer">Hub (⭐9.1k)</a> - Fastest unstructured dataset management for TensorFlow/PyTorch. Stream &amp; version-control data. Store even petabyte-scale data in a single numpy-like array on the cloud accessible on any machine. Visit <a href="https://activeloop.ai" rel="noopener noreferrer">activeloop.ai</a> for more info.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/6/"/>
    <summary>1 awesome projects updated on Feb 08 - Feb 14, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/5/</id>
    <title>Awesome Machine Learning Updates on Feb 01 - Feb 07, 2021</title>
    <updated>2021-02-05T21:06:13.000Z</updated>
    <published>2021-02-05T21:06:13.000Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://www.pinecone.io/" rel="noopener noreferrer">Pinecone</a> - Vector database for applications that require real-time, scalable vector embedding and similarity search.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/5/"/>
    <summary>1 awesome projects updated on Feb 01 - Feb 07, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/4/</id>
    <title>Awesome Machine Learning Updates on Jan 25 - Jan 31, 2021</title>
    <updated>2021-01-28T01:11:36.000Z</updated>
    <published>2021-01-27T12:31:13.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/dmey/synthia" rel="noopener noreferrer">Synthia (⭐66)</a> - Multidimensional synthetic data generation in Python.</li>
</ul>
<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/shobrook/sequitur" rel="noopener noreferrer">sequitur (⭐453)</a> PyTorch library for creating and training sequence autoencoders in just two lines of code</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/4/"/>
    <summary>2 awesome projects updated on Jan 25 - Jan 31, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/3/</id>
    <title>Awesome Machine Learning Updates on Jan 18 - Jan 24, 2021</title>
    <updated>2021-01-20T18:37:33.000Z</updated>
    <published>2021-01-20T18:37:33.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/RasaHQ/rasa" rel="noopener noreferrer">Rasa (⭐21k)</a> - A "machine learning framework to automate text-and voice-based conversations."</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/3/"/>
    <summary>1 awesome projects updated on Jan 18 - Jan 24, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/2/</id>
    <title>Awesome Machine Learning Updates on Jan 11 - Jan 17, 2021</title>
    <updated>2021-01-12T17:45:23.000Z</updated>
    <published>2021-01-12T17:45:23.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/gradio-app/gradio" rel="noopener noreferrer">Gradio (⭐42k)</a> - A Python library for quickly creating and sharing demos of models. Debug models interactively in your browser, get feedback from collaborators, and generate public links without deploying anything.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/2/"/>
    <summary>1 awesome projects updated on Jan 11 - Jan 17, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2021/1/</id>
    <title>Awesome Machine Learning Updates on Jan 04 - Jan 10, 2021</title>
    <updated>2021-01-07T10:14:41.000Z</updated>
    <published>2021-01-07T10:14:41.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/julianmack/Data_Assimilation" rel="noopener noreferrer">CAEs for Data Assimilation (⭐44)</a> - Convolutional autoencoders for 3D image/field compression applied to reduced order <a href="https://en.wikipedia.org/wiki/Data_assimilation" rel="noopener noreferrer">Data Assimilation</a>.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2021/1/"/>
    <summary>1 awesome projects updated on Jan 04 - Jan 10, 2021</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/52/</id>
    <title>Awesome Machine Learning Updates on Dec 28 - Jan 03, 2020</title>
    <updated>2020-12-26T03:59:36.000Z</updated>
    <published>2020-12-26T03:59:36.000Z</published>
    <content type="html"><![CDATA[<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/nikolaydubina/go-featureprocessing" rel="noopener noreferrer">go-featureprocessing (⭐126)</a> - Fast and convenient feature processing for low latency machine learning in Go.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/52/"/>
    <summary>1 awesome projects updated on Dec 28 - Jan 03, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/51/</id>
    <title>Awesome Machine Learning Updates on Dec 21 - Dec 27, 2020</title>
    <updated>2020-12-14T21:52:57.000Z</updated>
    <published>2020-12-14T21:52:57.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/gugarosa/learnergy" rel="noopener noreferrer">Learnergy (⭐69)</a> - Energy-based machine learning models built upon PyTorch.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/gugarosa/nalp" rel="noopener noreferrer">NALP (⭐24)</a> - A Natural Adversarial Language Processing framework built over Tensorflow.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/gugarosa/opfython" rel="noopener noreferrer">OPFython (⭐37)</a> - A Python-inspired implementation of the Optimum-Path Forest classifier.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/51/"/>
    <summary>3 awesome projects updated on Dec 21 - Dec 27, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/50/</id>
    <title>Awesome Machine Learning Updates on Dec 14 - Dec 20, 2020</title>
    <updated>2020-12-10T05:28:36.000Z</updated>
    <published>2020-12-10T05:28:36.000Z</published>
    <content type="html"><![CDATA[<h3><p>General-Purpose Machine Learning / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://gitlab.com/php-ai/php-ml" rel="noopener noreferrer">PHP-ML</a> - Machine Learning library for PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/50/"/>
    <summary>1 awesome projects updated on Dec 14 - Dec 20, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/48/</id>
    <title>Awesome Machine Learning Updates on Nov 30 - Dec 06, 2020</title>
    <updated>2020-11-23T03:44:10.000Z</updated>
    <published>2020-11-23T03:44:10.000Z</published>
    <content type="html"><![CDATA[<h3><p>C / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/xboot/libonnx" rel="noopener noreferrer">libonnx (⭐649)</a> - A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/48/"/>
    <summary>1 awesome projects updated on Nov 30 - Dec 06, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/45/</id>
    <title>Awesome Machine Learning Updates on Nov 09 - Nov 15, 2020</title>
    <updated>2020-11-02T07:42:59.000Z</updated>
    <published>2020-11-02T07:42:59.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/alan-turing-institute/sktime" rel="noopener noreferrer">sktime (⭐9.7k)</a> - A unified framework for machine learning with time series</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/45/"/>
    <summary>1 awesome projects updated on Nov 09 - Nov 15, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/43/</id>
    <title>Awesome Machine Learning Updates on Oct 26 - Nov 01, 2020</title>
    <updated>2020-10-25T09:01:12.000Z</updated>
    <published>2020-10-23T04:04:24.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/lightly-ai/lightly" rel="noopener noreferrer">lightly (⭐3.7k)</a> - Lightly is a computer vision framework for self-supervised learning.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://www.wandb.com/" rel="noopener noreferrer">Weights &amp; Biases</a> - Machine learning experiment tracking, dataset versioning, hyperparameter search, visualization, and collaboration</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/43/"/>
    <summary>2 awesome projects updated on Oct 26 - Nov 01, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/42/</id>
    <title>Awesome Machine Learning Updates on Oct 19 - Oct 25, 2020</title>
    <updated>2020-10-14T10:48:40.000Z</updated>
    <published>2020-10-14T10:48:40.000Z</published>
    <content type="html"><![CDATA[<h3><p>Clojure / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://gitlab.com/alanmarazzi/clj-boost" rel="noopener noreferrer">clj-boost</a> - Wrapper for XGBoost</li>
</ul>

<ul>
<li><a href="https://github.com/cloudkj/lambda-ml" rel="noopener noreferrer">lambda-ml (⭐78)</a> - Simple, concise implementations of machine learning techniques and utilities in Clojure.</li>
</ul>
<h3><p>Clojure / Deep Learning</p>
</h3>
<ul>
<li><a href="https://mxnet.apache.org/versions/1.7.0/api/clojure" rel="noopener noreferrer">MXNet</a> - Bindings to Apache MXNet - part of the MXNet project</li>
</ul>

<ul>
<li><a href="https://github.com/uncomplicate/deep-diamond" rel="noopener noreferrer">Deep Diamond (⭐460)</a> - A fast Clojure Tensor &amp; Deep Learning library</li>
</ul>

<ul>
<li><a href="https://github.com/hswick/jutsu.ai" rel="noopener noreferrer">jutsu.ai (⭐101)</a> - Clojure wrapper for deeplearning4j with some added syntactic sugar.</li>
</ul>

<ul>
<li><a href="https://github.com/yetanalytics/dl4clj" rel="noopener noreferrer">dl4clj (⭐99)</a> - Clojure wrapper for Deeplearning4j.</li>
</ul>
<h3><p>Clojure / Data Analysis</p>
</h3>
<ul>
<li><a href="https://github.com/scicloj/tablecloth" rel="noopener noreferrer">Tablecloth (⭐358)</a> - A dataframe grammar wrapping tech.ml.dataset, inspired by several R libraries</li>
</ul>

<ul>
<li><a href="https://github.com/alanmarazzi/panthera" rel="noopener noreferrer">Panthera (⭐191)</a> - Clojure API wrapping Python's Pandas library</li>
</ul>

<ul>
<li><a href="https://github.com/zero-one-group/geni" rel="noopener noreferrer">Geni (⭐294)</a> - a Clojure dataframe library that runs on Apache Spark</li>
</ul>
<h3><p>Clojure / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/jsa-aerial/hanami" rel="noopener noreferrer">Hanami (⭐408)</a> - Clojure(Script) library and framework for creating interactive visualization applications based in Vega-Lite (VGL) and/or Vega (VG) specifications. Automatic framing and layouts along with a powerful templating system for abstracting visualization specs</li>
</ul>

<ul>
<li><a href="https://github.com/jsa-aerial/saite" rel="noopener noreferrer">Saite (⭐141)</a> -  Clojure(Script) client/server application for dynamic interactive explorations and the creation of live shareable documents capturing them using Vega/Vega-Lite, CodeMirror, markdown, and LaTeX</li>
</ul>

<ul>
<li><a href="https://github.com/metasoarous/oz" rel="noopener noreferrer">Oz (⭐835)</a> - Data visualisation using Vega/Vega-Lite and Hiccup, and a live-reload platform for literate-programming</li>
</ul>

<ul>
<li><a href="https://github.com/clojupyter/clojupyter" rel="noopener noreferrer">clojupyter (⭐860)</a> -  A Jupyter kernel for Clojure - run Clojure code in Jupyter Lab, Notebook and Console.</li>
</ul>
<h3><p>Clojure / Interop</p>
</h3>
<ul>
<li><a href="https://clojure.org/reference/java_interop" rel="noopener noreferrer">Java Interop</a> - Clojure has Native Java Interop from which Java's ML ecosystem can be accessed</li>
</ul>

<ul>
<li><a href="https://clojurescript.org/reference/javascript-api" rel="noopener noreferrer">JavaScript Interop</a> - ClojureScript has Native JavaScript Interop from which JavaScript's ML ecosystem can be accessed</li>
</ul>

<ul>
<li><a href="https://github.com/clj-python/libpython-clj" rel="noopener noreferrer">Libpython-clj (⭐1.2k)</a> - Interop with Python</li>
</ul>

<ul>
<li><a href="https://github.com/scicloj/clojisr" rel="noopener noreferrer">ClojisR (⭐159)</a> - Interop with R and Renjin (R on the JVM)</li>
</ul>
<h3><p>Clojure / Misc</p>
</h3>
<ul>
<li><a href="https://neanderthal.uncomplicate.org/" rel="noopener noreferrer">Neanderthal</a> - Fast Clojure Matrix Library (native CPU, GPU, OpenCL, CUDA)</li>
</ul>

<ul>
<li><a href="https://github.com/generateme/fastmath" rel="noopener noreferrer">fastmath (⭐278)</a> - A collection of functions for mathematical and statistical computing, macine learning, etc., wrapping several JVM libraries</li>
</ul>

<ul>
<li><a href="https://github.com/atisharma/matlib" rel="noopener noreferrer">matlib (⭐26)</a> - A Clojure library of optimisation and control theory tools and convenience functions based on Neanderthal.</li>
</ul>
<h3><p>Clojure / Extra</p>
</h3>
<ul>
<li><a href="https://scicloj.github.io/pages/libraries/" rel="noopener noreferrer">Scicloj</a> - Curated list of ML related resources for Clojure.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/42/"/>
    <summary>21 awesome projects updated on Oct 19 - Oct 25, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/41/</id>
    <title>Awesome Machine Learning Updates on Oct 12 - Oct 18, 2020</title>
    <updated>2020-10-11T21:48:01.000Z</updated>
    <published>2020-10-11T09:55:17.000Z</published>
    <content type="html"><![CDATA[<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://haifengl.github.io/" rel="noopener noreferrer">Smile</a> - Statistical Machine Intelligence and Learning Engine.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/nidhaloff/igel" rel="noopener noreferrer">igel (⭐3.1k)</a> -&gt; A delightful machine learning tool that allows you to train/fit, test and use models <strong>without writing code</strong></li>
</ul>
<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/zueve/neurolab" rel="noopener noreferrer">TResNet: Simple and powerful neural network library for python (⭐167)</a> - Variety of supported types of Artificial Neural Network and learning algorithms.</li>
</ul>
<h3><p>Ruby / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://sourceforge.net/projects/raspell/" rel="noopener noreferrer">Raspell</a> - raspell is an interface binding for ruby. <strong>[Deprecated]</strong></li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/41/"/>
    <summary>4 awesome projects updated on Oct 12 - Oct 18, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/40/</id>
    <title>Awesome Machine Learning Updates on Oct 05 - Oct 11, 2020</title>
    <updated>2020-10-03T20:37:16.000Z</updated>
    <published>2020-10-01T05:53:06.000Z</published>
    <content type="html"><![CDATA[<h3><p>C / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/alrevuelta/cONNXr" rel="noopener noreferrer">cONNXr (⭐217)</a> - An <code>ONNX</code> runtime written in pure C (99) with zero dependencies focused on small embedded devices. Run inference on your machine learning models no matter which framework you train it with. Easy to install and compiles everywhere, even in very old devices.</li>
</ul>
<h3><p>C / Computer Vision</p>
</h3>
<ul>
<li><a href="http://www.vlfeat.org/" rel="noopener noreferrer">VLFeat</a> - VLFeat is an open and portable library of computer vision algorithms, which has a Matlab toolbox.</li>
</ul>
<h3><p>C++ / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/ukoethe/vigra" rel="noopener noreferrer">VIGRA (⭐438)</a> - VIGRA is a genertic cross-platform C++ computer vision and machine learning library for volumes of arbitrary dimensionality with Python bindings.</li>
</ul>
<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Tyill/skynet" rel="noopener noreferrer">skynet (⭐62)</a> - A library for learning neural networks, has C-interface, net set in JSON. Written in C++ with bindings in Python, C++ and C#.</li>
</ul>

<ul>
<li><a href="https://github.com/logicalclocks/hopsworks" rel="noopener noreferrer">Hopsworks (⭐1.3k)</a> - A data-intensive platform for AI with the industry's first open-source feature store. The Hopsworks Feature Store provides both a feature warehouse for training and batch based on Apache Hive and a feature serving database, based on MySQL Cluster, for online applications.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/proycon/colibri-core" rel="noopener noreferrer">colibri-core (⭐129)</a> - Python binding to C++ library for extracting and working with basic linguistic constructions such as n-grams and skipgrams in a quick and memory-efficient way.</li>
</ul>

<ul>
<li><a href="https://github.com/duanhongyi/genius" rel="noopener noreferrer">genius (⭐234)</a> - A Chinese segment based on Conditional Random Field.</li>
</ul>

<ul>
<li><a href="https://github.com/EducationalTestingService/python-zpar" rel="noopener noreferrer">python-zpar (⭐50)</a> - Python bindings for <a href="https://github.com/frcchang/zpar" rel="noopener noreferrer">ZPar (⭐136)</a>, a statistical part-of-speech-tagger, constituency parser, and dependency parser for English.</li>
</ul>

<ul>
<li><a href="https://github.com/deepmipt/DeepPavlov/" rel="noopener noreferrer">DeepPavlov (⭐7k)</a> - conversational AI library with many pre-trained Russian NLP models.</li>
</ul>
<h3><p>C++ / Sequence Analysis</p>
</h3>
<ul>
<li><a href="https://github.com/ayoshiaki/tops" rel="noopener noreferrer">ToPS (⭐37)</a> - This is an object-oriented framework that facilitates the integration of probabilistic models for sequences over a user defined alphabet. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/songtianyi/go-mxnet-predictor" rel="noopener noreferrer">go-mxnet-predictor (⭐54)</a> - Go binding for MXNet c_predict_api to do inference with a pre-trained model.</li>
</ul>
<h3><p>Java / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://ctakes.apache.org/" rel="noopener noreferrer">Apache cTAKES</a> - Apache Clinical Text Analysis and Knowledge Extraction System (cTAKES) is an open-source natural language processing system for information extraction from electronic medical record clinical free-text.</li>
</ul>
<h3><p>Julia / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/JuliaStats/SVM.jl" rel="noopener noreferrer">SVM (⭐40)</a> - SVM for Julia. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Matlab / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://amplab.cs.berkeley.edu/an-nlp-library-for-matlab/" rel="noopener noreferrer">NLP</a> - A NLP library for Matlab.</li>
</ul>
<h3><p>.NET / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://dotnet.github.io/infer/" rel="noopener noreferrer">Infer.NET</a> - Infer.NET is a framework for running Bayesian inference in graphical models. One can use Infer.NET to solve many different kinds of machine learning problems, from standard problems like classification, recommendation or clustering through customized solutions to domain-specific problems. Infer.NET has been used in a wide variety of domains including information retrieval, bioinformatics, epidemiology, vision, and many others.</li>
</ul>

<ul>
<li><a href="https://sourceforge.net/projects/nnd/" rel="noopener noreferrer">Neural Network Designer</a> - DBMS management system and designer for neural networks. The designer application is developed using WPF, and is a user interface which allows you to design your neural network, query the network, create and configure chat bots that are capable of asking questions and learning from your feedback. The chat bots can even scrape the internet for information to return in their output as well as to use for learning.</li>
</ul>

<ul>
<li><a href="https://github.com/mrdimosthenis/Synapses" rel="noopener noreferrer">Synapses (⭐73)</a> - Neural network library in F#.</li>
</ul>
<h3><p>.NET / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.nuget.org/packages/MathNet.Numerics/" rel="noopener noreferrer">Math.NET Numerics</a> - Numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and everyday use. Supports .Net 4.0, .Net 3.5 and Mono on Windows, Linux and Mac; Silverlight 5, WindowsPhone/SL 8, WindowsPhone 8.1 and Windows 8 with PCL Portable Profiles 47 and 344; Android/iOS with Xamarin.</li>
</ul>
<h3><p>General-Purpose Machine Learning / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/nikolaypavlov/MLPNeuralNet" rel="noopener noreferrer">MLPNeuralNet (⭐900)</a> - Fast multilayer perceptron neural network library for iOS and Mac OS X. MLPNeuralNet predicts new examples by trained neural networks. It is built on top of the Apple's Accelerate Framework, using vectorized operations and hardware acceleration if available. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/Kalvar/ios-BPN-NeuralNetwork" rel="noopener noreferrer">BPN-NeuralNetwork (⭐33)</a> - It implemented 3 layers of neural networks ( Input Layer, Hidden Layer and Output Layer ) and it was named Back Propagation Neural Networks (BPN). This network can be used in products recommendation, user behavior analysis, data mining and data analysis. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/Kalvar/ios-Multi-Perceptron-NeuralNetwork" rel="noopener noreferrer">Multi-Perceptron-NeuralNetwork (⭐24)</a> - It implemented multi-perceptrons neural network (ニューラルネットワーク) based on Back Propagation Neural Networks (BPN) and designed unlimited-hidden-layers.</li>
</ul>

<ul>
<li><a href="https://github.com/Kalvar/ios-KRHebbian-Algorithm" rel="noopener noreferrer">KRHebbian-Algorithm (⭐13)</a> - It is a non-supervisory and self-learning algorithm (adjust the weights) in the neural network of Machine Learning. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/Kalvar/ios-KRKmeans-Algorithm" rel="noopener noreferrer">KRKmeans-Algorithm (⭐23)</a> - It implemented K-Means  clustering and classification algorithm. It could be used in data mining and image compression. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/ageitgey/face_recognition" rel="noopener noreferrer">face_recognition (⭐56k)</a> - Face recognition library that recognizes and manipulates faces from Python or from the command line.</li>
</ul>

<ul>
<li><a href="https://github.com/jrosebr1/imutils" rel="noopener noreferrer">imutils (⭐4.6k)</a> - A library containing Convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Shanky-21/Machine_learning" rel="noopener noreferrer">ML Model building (⭐35)</a> -&gt; A Repository Containing Classification, Clustering, Regression, Recommender Notebooks with illustration to make them.</li>
</ul>

<ul>
<li><a href="https://github.com/neptune-ml/steppy" rel="noopener noreferrer">steppy (⭐136)</a> -&gt; Lightweight, Python library for fast and reproducible machine learning experimentation. Introduces a very simple interface that enables clean machine learning pipeline design.</li>
</ul>

<ul>
<li><a href="https://github.com/simpleai-team/simpleai" rel="noopener noreferrer">SimpleAI (⭐989)</a> Python implementation of many of the artificial intelligence algorithms described in the book "Artificial Intelligence, a Modern Approach". It focuses on providing an easy to use, well documented and tested library.</li>
</ul>

<ul>
<li><a href="https://github.com/raamana/neuropredict" rel="noopener noreferrer">neuropredict (⭐104)</a> - Aimed at novice machine learners and non-expert programmers, this package offers easy (no coding needed) and comprehensive machine learning (evaluation and full report of predictive performance WITHOUT requiring you to code) in Python for NeuroImaging and any other type of features. This is aimed at absorbing much of the ML workflow, unlike other packages like nilearn and pymvpa, which require you to learn their API and code to produce anything useful.</li>
</ul>

<ul>
<li><a href="https://imbalanced-learn.org/stable/" rel="noopener noreferrer">imbalanced-learn</a> - Python module to perform under sampling and oversampling with various techniques.</li>
</ul>

<ul>
<li><a href="https://github.com/fukatani/stacked_generalization" rel="noopener noreferrer">stacked_generalization (⭐119)</a> - Implementation of machine learning stacking technique as a handy library in Python.</li>
</ul>

<ul>
<li><a href="https://github.com/OpenMined/PyGrid/" rel="noopener noreferrer">PyGrid (⭐614)</a> - Peer-to-peer network of data owners and data scientists who can collectively train AI models using PySyft</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/Shanky-21/Data_visualization" rel="noopener noreferrer">DataVisualization (⭐49)</a> - A GitHub Repository Where you can Learn Datavisualizatoin Basics to Intermediate level.</li>
</ul>

<ul>
<li><a href="https://github.com/mars-project/mars" rel="noopener noreferrer">Mars (⭐2.7k)</a> - A tensor-based framework for large-scale data computation which is often regarded as a parallel and distributed version of NumPy.</li>
</ul>

<ul>
<li><a href="https://github.com/rewonc/pastalog" rel="noopener noreferrer">pastalog (⭐421)</a> - Simple, realtime visualization of neural network training performance.</li>
</ul>
<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://cran.r-project.org/web/packages/party/index.html" rel="noopener noreferrer">party</a> - party: A Laboratory for Recursive Partitioning</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/partykit/index.html" rel="noopener noreferrer">partykit</a> - partykit: A Toolkit for Recursive Partitioning.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/IDSIA/sacred" rel="noopener noreferrer">Sacred (⭐4.4k)</a> - Python tool to help  you configure, organize, log and reproduce experiments. Like a notebook lab in the context of Chemistry/Biology. The community has built multiple add-ons leveraging the proposed standard.</li>
</ul>

<ul>
<li><a href="https://mlflow.org/" rel="noopener noreferrer">MLFlow</a> - platform to manage the ML lifecycle, including experimentation, reproducibility and deployment. Framework and language agnostic, take a look at all the built-in integrations.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/40/"/>
    <summary>39 awesome projects updated on Oct 05 - Oct 11, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/39/</id>
    <title>Awesome Machine Learning Updates on Sep 28 - Oct 04, 2020</title>
    <updated>2020-09-27T11:03:43.000Z</updated>
    <published>2020-09-27T11:03:43.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/madmaze/pytesseract" rel="noopener noreferrer">pytessarct (⭐6.3k)</a> - Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and "read" the text embedded in images. Python-tesseract is a wrapper for <a href="https://github.com/tesseract-ocr/tesseract" rel="noopener noreferrer">Google's Tesseract-OCR Engine (⭐74k)</a>.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/39/"/>
    <summary>1 awesome projects updated on Sep 28 - Oct 04, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/38/</id>
    <title>Awesome Machine Learning Updates on Sep 21 - Sep 27, 2020</title>
    <updated>2020-09-20T19:23:01.000Z</updated>
    <published>2020-09-15T20:14:53.000Z</published>
    <content type="html"><![CDATA[<h3><p>Fortran / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/modern-fortran/neural-fortran" rel="noopener noreferrer">neural-fortran (⭐467)</a> - A parallel neural net microframework.
Read the paper <a href="https://arxiv.org/abs/1902.06714" rel="noopener noreferrer">here</a>.</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/cdslaborg/paramonte" rel="noopener noreferrer">ParaMonte (⭐304)</a> - A general-purpose Python library for Bayesian data analysis and visualization via serial/parallel Monte Carlo and MCMC simulations. Documentation can be found <a href="https://www.cdslab.org/paramonte/" rel="noopener noreferrer">here</a>.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/clips/pattern" rel="noopener noreferrer">Pattern (⭐8.9k)</a> - A web mining module for the Python programming language. It has tools for natural language processing, machine learning, among others.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/skorch-dev/skorch" rel="noopener noreferrer">skorch (⭐6.2k)</a> - A scikit-learn compatible neural network library that wraps PyTorch.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/LiYangHart/Hyperparameter-Optimization-of-Machine-Learning-Algorithms" rel="noopener noreferrer">Hyperparameter-Optimization-of-Machine-Learning-Algorithms (⭐1.3k)</a> - Code for hyperparameter tuning/optimization of machine learning and deep learning algorithms.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/38/"/>
    <summary>5 awesome projects updated on Sep 21 - Sep 27, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/37/</id>
    <title>Awesome Machine Learning Updates on Sep 14 - Sep 20, 2020</title>
    <updated>2020-09-11T15:50:27.000Z</updated>
    <published>2020-09-11T14:50:34.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html" rel="noopener noreferrer">Self-supervised learning</a></li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/PyTorchLightning/deep-learning-project-template" rel="noopener noreferrer">ML/DL project template (⭐1.3k)</a></li>
</ul>

<ul>
<li><a href="https://github.com/PyTorchLightning/pytorch-lightning" rel="noopener noreferrer">PyTorch Lightning (⭐31k)</a> - The lightweight PyTorch wrapper for high-performance AI research.</li>
</ul>

<ul>
<li><a href="https://github.com/PyTorchLightning/pytorch-lightning-bolts" rel="noopener noreferrer">PyTorch Lightning Bolts (⭐1.8k)</a> - Toolbox of models, callbacks, and datasets for AI/ML researchers.</li>
</ul>

<ul>
<li><a href="https://github.com/determined-ai/determined" rel="noopener noreferrer">Determined (⭐3.2k)</a> - Scalable deep learning training platform, including integrated support for distributed training, hyperparameter tuning, experiment tracking, and model management.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/37/"/>
    <summary>5 awesome projects updated on Sep 14 - Sep 20, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/36/</id>
    <title>Awesome Machine Learning Updates on Sep 07 - Sep 13, 2020</title>
    <updated>2020-09-03T14:24:01.000Z</updated>
    <published>2020-09-02T08:16:07.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/couler-proj/couler" rel="noopener noreferrer">Couler (⭐942)</a> - Unified interface for constructing and managing machine learning workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.</li>
</ul>

<ul>
<li><a href="https://github.com/alirezamika/evostra" rel="noopener noreferrer">evostra (⭐274)</a> - A fast Evolution Strategy implementation in Python.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://pythonizr.com" rel="noopener noreferrer">Pythonizr</a> - An online tool to generate boilerplate machine learning code that uses scikit-learn.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/36/"/>
    <summary>3 awesome projects updated on Sep 07 - Sep 13, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/34/</id>
    <title>Awesome Machine Learning Updates on Aug 24 - Aug 30, 2020</title>
    <updated>2020-08-21T16:11:06.000Z</updated>
    <published>2020-08-18T13:56:49.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/guofei9987/scikit-opt" rel="noopener noreferrer">Scikit-Opt (⭐6.4k)</a> - Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm, Artificial Fish Swarm Algorithm in Python)</li>
</ul>

<ul>
<li><a href="https://github.com/leoxiaobin/deep-high-resolution-net.pytorch" rel="noopener noreferrer">Deep High-Resolution-Net (⭐4.5k)</a> - A PyTorch implementation of CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"</li>
</ul>

<ul>
<li><a href="https://github.com/ProGamerGov/dream-creator" rel="noopener noreferrer">dream-creator (⭐71)</a> - A PyTorch implementation of DeepDream. Allows individuals to quickly and easily train their own custom GoogleNet models with custom datasets for DeepDream.</li>
</ul>

<ul>
<li><a href="https://github.com/greentfrapp/lucent" rel="noopener noreferrer">Lucent (⭐655)</a> - Tensorflow and OpenAI Clarity's Lucid adapted for PyTorch.</li>
</ul>
<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://spinningup.openai.com" rel="noopener noreferrer">Spinning Up</a> - An educational resource designed to let anyone learn to become a skilled practitioner in deep reinforcement learning</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/34/"/>
    <summary>5 awesome projects updated on Aug 24 - Aug 30, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/29/</id>
    <title>Awesome Machine Learning Updates on Jul 20 - Jul 26, 2020</title>
    <updated>2020-07-17T23:56:58.000Z</updated>
    <published>2020-07-17T19:40:38.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/benedekrozemberczki/pytorch_geometric_temporal" rel="noopener noreferrer">PyTorch Geometric Temporal (⭐3k)</a> -&gt; A temporal extension of PyTorch Geometric for dynamic graph representation learning.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/iterative/cml" rel="noopener noreferrer">CML (⭐4.2k)</a> - A library for doing continuous integration with ML projects. Use GitHub Actions &amp; GitLab CI to train and evaluate models in production like environments and automatically generate visual reports with metrics and graphs in pull/merge requests. Framework &amp; language agnostic.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/29/"/>
    <summary>2 awesome projects updated on Jul 20 - Jul 26, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/28/</id>
    <title>Awesome Machine Learning Updates on Jul 13 - Jul 19, 2020</title>
    <updated>2020-07-11T02:18:44.000Z</updated>
    <published>2020-07-06T19:53:15.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://scitools.org.uk/cartopy/docs/latest/" rel="noopener noreferrer">Cartopy</a> - Cartopy is a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses.</li>
</ul>
<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://deepmind.com/research/publications/Acme" rel="noopener noreferrer">acme</a> - An Open Source Distributed Framework for Reinforcement Learning that makes build and train your agents easily.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://chrome.google.com/webstore/detail/code-finder-for-research/aikkeehnlfpamidigaffhfmgbkdeheil" rel="noopener noreferrer">CatalyzeX</a> - Browser extension (<a href="https://chrome.google.com/webstore/detail/code-finder-for-research/aikkeehnlfpamidigaffhfmgbkdeheil" rel="noopener noreferrer">Chrome</a> and <a href="https://addons.mozilla.org/en-US/firefox/addon/code-finder-catalyzex/" rel="noopener noreferrer">Firefox</a>) that automatically finds and shows code implementations for machine learning papers anywhere: Google, Twitter, Arxiv, Scholar, etc.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/28/"/>
    <summary>3 awesome projects updated on Jul 13 - Jul 19, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/23/</id>
    <title>Awesome Machine Learning Updates on Jun 08 - Jun 14, 2020</title>
    <updated>2020-06-04T06:19:17.000Z</updated>
    <published>2020-06-04T06:19:17.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/kennysong/minigrad" rel="noopener noreferrer">MiniGrad (⭐99)</a> – A minimal, educational, Pythonic implementation of autograd (~100 loc).</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/23/"/>
    <summary>1 awesome projects updated on Jun 08 - Jun 14, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/21/</id>
    <title>Awesome Machine Learning Updates on May 25 - May 31, 2020</title>
    <updated>2020-05-22T22:38:38.000Z</updated>
    <published>2020-05-18T12:40:40.000Z</published>
    <content type="html"><![CDATA[<h3><p>.NET / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/tech-quantum/MxNet.Sharp" rel="noopener noreferrer">MxNet.Sharp (⭐151)</a> - .NET Standard bindings for Apache MxNet with Imperative, Symbolic and Gluon Interface for developing, training and deploying Machine Learning models in C#. <a href="https://mxnet.tech-quantum.com/" rel="noopener noreferrer">https://mxnet.tech-quantum.com/</a></li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/benedekrozemberczki/littleballoffur" rel="noopener noreferrer">Little Ball of Fur (⭐713)</a> -&gt; A graph sampling extension library for NetworkX with a Scikit-Learn like API.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/21/"/>
    <summary>2 awesome projects updated on May 25 - May 31, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/20/</id>
    <title>Awesome Machine Learning Updates on May 18 - May 24, 2020</title>
    <updated>2020-05-15T16:16:13.000Z</updated>
    <published>2020-05-14T06:03:06.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/CMU-Perceptual-Computing-Lab/openpose" rel="noopener noreferrer">Openpose (⭐34k)</a> - A real-time multi-person keypoint detection library for body, face, hands, and foot estimation</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://implicit.readthedocs.io/en/latest/quickstart.html" rel="noopener noreferrer">implicit</a> - Fast Python Collaborative Filtering for Implicit Datasets.</li>
</ul>

<ul>
<li><a href="https://making.lyst.com/lightfm/docs/home.html" rel="noopener noreferrer">LightFM</a> -  A Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback.</li>
</ul>

<ul>
<li><a href="https://github.com/mljar/mljar-supervised" rel="noopener noreferrer">mljar-supervised (⭐3.3k)</a> - An Automated Machine Learning (AutoML) python package for tabular data. It can handle: Binary Classification, MultiClass Classification and Regression. It provides explanations and markdown reports.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/20/"/>
    <summary>4 awesome projects updated on May 18 - May 24, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/17/</id>
    <title>Awesome Machine Learning Updates on Apr 27 - May 03, 2020</title>
    <updated>2020-04-24T09:47:25.000Z</updated>
    <published>2020-04-24T09:47:25.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/jungtaekkim/bayeso" rel="noopener noreferrer">bayeso (⭐95)</a> - A simple, but essential Bayesian optimization package, written in Python.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/17/"/>
    <summary>1 awesome projects updated on Apr 27 - May 03, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/16/</id>
    <title>Awesome Machine Learning Updates on Apr 20 - Apr 26, 2020</title>
    <updated>2020-04-15T11:36:29.000Z</updated>
    <published>2020-04-15T11:36:29.000Z</published>
    <content type="html"><![CDATA[<h3><p>Ruby / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/yoshoku/rumale" rel="noopener noreferrer">rumale (⭐908)</a> - Rumale is a machine learning library in Ruby</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/16/"/>
    <summary>1 awesome projects updated on Apr 20 - Apr 26, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/15/</id>
    <title>Awesome Machine Learning Updates on Apr 13 - Apr 19, 2020</title>
    <updated>2020-04-11T02:06:46.000Z</updated>
    <published>2020-04-11T02:06:46.000Z</published>
    <content type="html"><![CDATA[<h3><p>Go / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/rocketlaunchr/dataframe-go" rel="noopener noreferrer">dataframe-go (⭐1.3k)</a> - Dataframes for machine-learning and statistics (similar to pandas).</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/15/"/>
    <summary>1 awesome projects updated on Apr 13 - Apr 19, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/14/</id>
    <title>Awesome Machine Learning Updates on Apr 06 - Apr 12, 2020</title>
    <updated>2020-04-01T00:59:58.000Z</updated>
    <published>2020-04-01T00:59:58.000Z</published>
    <content type="html"><![CDATA[<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/aunum/goro" rel="noopener noreferrer">goro (⭐374)</a> - A high-level machine learning library in the vein of Keras.</li>
</ul>
<h3><p>Go / Reinforcement learning</p>
</h3>
<ul>
<li><a href="https://github.com/aunum/gold" rel="noopener noreferrer">gold (⭐351)</a> - A reinforcement learning library.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/14/"/>
    <summary>2 awesome projects updated on Apr 06 - Apr 12, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/12/</id>
    <title>Awesome Machine Learning Updates on Mar 23 - Mar 29, 2020</title>
    <updated>2020-03-20T01:02:40.000Z</updated>
    <published>2020-03-16T19:24:44.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/alibaba/pipcook" rel="noopener noreferrer">Pipcook (⭐2.6k)</a> - A JavaScript application framework for machine learning and its engineering.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/ProGamerGov/neural-dream" rel="noopener noreferrer">neural-dream (⭐148)</a> - A PyTorch implementation of DeepDream.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/mindsdb/lightwood" rel="noopener noreferrer">Lightwood (⭐507)</a> - A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glued together seamlessly with objective to build predictive models with one line of code.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/12/"/>
    <summary>3 awesome projects updated on Mar 23 - Mar 29, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/8/</id>
    <title>Awesome Machine Learning Updates on Feb 24 - Mar 01, 2020</title>
    <updated>2020-02-22T15:39:55.000Z</updated>
    <published>2020-02-22T15:39:55.000Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/BayesWitnesses/m2cgen" rel="noopener noreferrer">m2cgen (⭐3k)</a> - A tool that allows the conversion of ML models into native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart) with zero dependencies.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/8/"/>
    <summary>1 awesome projects updated on Feb 24 - Mar 01, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/5/</id>
    <title>Awesome Machine Learning Updates on Feb 03 - Feb 09, 2020</title>
    <updated>2020-02-01T00:51:50.000Z</updated>
    <published>2020-01-27T17:14:56.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/benedekrozemberczki/karateclub" rel="noopener noreferrer">Karate Club (⭐2.3k)</a> -&gt; An unsupervised machine learning extension library for NetworkX with a Scikit-Learn like API.</li>
</ul>

<ul>
<li><a href="https://github.com/NervanaSystems/neon" rel="noopener noreferrer">neon (⭐3.9k)</a> - Nervana's <a href="https://github.com/soumith/convnet-benchmarks" rel="noopener noreferrer">high-performance (⭐2.7k)</a> Python-based Deep Learning framework [DEEP LEARNING]. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://www.manning.com/books/machine-learning-with-tensorflow-second-edition" rel="noopener noreferrer">MachineLearningWithTensorFlow2ed</a> - a book on general purpose machine learning techniques regression, classification, unsupervised clustering, reinforcement learning, auto encoders, convolutional neural networks, RNNs, LSTMs, using TensorFlow 1.14.1.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/5/"/>
    <summary>3 awesome projects updated on Feb 03 - Feb 09, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/4/</id>
    <title>Awesome Machine Learning Updates on Jan 27 - Feb 02, 2020</title>
    <updated>2020-01-24T04:57:53.000Z</updated>
    <published>2020-01-23T21:01:01.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/facebookresearch/Detectron" rel="noopener noreferrer">Detectron (⭐26k)</a> - FAIR's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/alankbi/detecto" rel="noopener noreferrer">Detecto (⭐625)</a> - Train and run a computer vision model with 5-10 lines of code.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/sergioburdisso/pyss3" rel="noopener noreferrer">PySS3 (⭐349)</a> - Python package that implements a novel white-box machine learning model for text classification, called SS3. Since SS3 has the ability to visually explain its rationale, this package also comes with easy-to-use interactive visualizations tools (<a href="http://tworld.io/ss3/" rel="noopener noreferrer">online demos</a>).</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/4/"/>
    <summary>3 awesome projects updated on Jan 27 - Feb 02, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2020/2/</id>
    <title>Awesome Machine Learning Updates on Jan 13 - Jan 19, 2020</title>
    <updated>2020-01-07T15:18:09.000Z</updated>
    <published>2020-01-07T15:18:09.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/AutoViML/Auto_ViML" rel="noopener noreferrer">Auto_ViML (⭐546)</a> -&gt; Automatically Build Variant Interpretable ML models fast! Auto_ViML is pronounced "auto vimal", is a comprehensive and scalable Python AutoML toolkit with imbalanced handling, ensembling, stacking and built-in feature selection. Featured in <a href="https://towardsdatascience.com/why-automl-is-an-essential-new-tool-for-data-scientists-2d9ab4e25e46?source=friends_link&amp;sk=d03a0cc55c23deb497d546d6b9be0653">Medium article</a>.</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/AutoViML/AutoViz" rel="noopener noreferrer">AutoViz (⭐1.9k)</a> AutoViz performs automatic visualization of any dataset with a single line of Python code. Give it any input file (CSV, txt or JSON) of any size and AutoViz will visualize it. See <a href="https://towardsdatascience.com/autoviz-a-new-tool-for-automated-visualization-ec9c1744a6ad?source=friends_link&amp;sk=c9e9503ec424b191c6096d7e3f515d10">Medium article</a>.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2020/2/"/>
    <summary>2 awesome projects updated on Jan 13 - Jan 19, 2020</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/51/</id>
    <title>Awesome Machine Learning Updates on Dec 23 - Dec 29, 2019</title>
    <updated>2019-12-20T17:04:42.000Z</updated>
    <published>2019-12-20T17:04:42.000Z</published>
    <content type="html"><![CDATA[<h3><p>R / Data Manipulation | Data Analysis | Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.rdocumentation.org/packages/dplyr/versions/0.7.8" rel="noopener noreferrer">dplyr</a> - A data manipulation package that helps to solve the most common data manipulation problems.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/51/"/>
    <summary>1 awesome projects updated on Dec 23 - Dec 29, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/49/</id>
    <title>Awesome Machine Learning Updates on Dec 09 - Dec 15, 2019</title>
    <updated>2019-12-05T00:50:26.000Z</updated>
    <published>2019-12-05T00:50:26.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/scikit-multiflow/scikit-multiflow" rel="noopener noreferrer">scikit-multiflow (⭐793)</a> - A machine learning framework for multi-output/multi-label and stream data.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/49/"/>
    <summary>1 awesome projects updated on Dec 09 - Dec 15, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/45/</id>
    <title>Awesome Machine Learning Updates on Nov 11 - Nov 17, 2019</title>
    <updated>2019-11-07T00:48:35.000Z</updated>
    <published>2019-11-07T00:48:35.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/rlworkgroup/dowel" rel="noopener noreferrer">dowel (⭐35)</a> - A little logger for machine learning research. Output any object to the terminal, CSV, TensorBoard, text logs on disk, and more with just one call to <code>logger.log()</code>.</li>
</ul>
<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/rlworkgroup/garage" rel="noopener noreferrer">garage (⭐2.1k)</a> - A toolkit for reproducible reinforcement learning research</li>
</ul>

<ul>
<li><a href="https://github.com/rlworkgroup/metaworld" rel="noopener noreferrer">metaworld (⭐1.8k)</a> - An open source robotics benchmark for meta- and multi-task reinforcement learning</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/45/"/>
    <summary>3 awesome projects updated on Nov 11 - Nov 17, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/44/</id>
    <title>Awesome Machine Learning Updates on Nov 04 - Nov 10, 2019</title>
    <updated>2019-11-03T14:26:00.000Z</updated>
    <published>2019-10-31T13:29:26.000Z</published>
    <content type="html"><![CDATA[<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/zhenghaoz/gorse" rel="noopener noreferrer">gorse (⭐8)</a> - An offline recommender system backend based on collaborative filtering written in Go.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/lisa-lab/pylearn2" rel="noopener noreferrer">Pylearn2 (⭐2.8k)</a> - A Machine Learning library based on <a href="https://github.com/Theano/Theano" rel="noopener noreferrer">Theano (⭐10k)</a>. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/quantumblacklabs/kedro/" rel="noopener noreferrer">Kedro (⭐11k)</a> - Kedro is a data and development workflow framework that implements best practices for data pipelines with an eye towards productionizing machine learning models.</li>
</ul>

<ul>
<li><a href="https://guild.ai/" rel="noopener noreferrer">guild.ai</a> - Tool to log, analyze, compare and "optimize" experiments. It's cross-platform and framework independent, and provided integrated visualizers such as tensorboard.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/44/"/>
    <summary>4 awesome projects updated on Nov 04 - Nov 10, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/43/</id>
    <title>Awesome Machine Learning Updates on Oct 28 - Nov 03, 2019</title>
    <updated>2019-10-27T12:12:14.000Z</updated>
    <published>2019-10-27T12:12:14.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/fastai/fastai" rel="noopener noreferrer">Fastai (⭐28k)</a> - High-level wrapper built on the top of Pytorch which supports vision, text, tabular data and collaborative filtering.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/43/"/>
    <summary>1 awesome projects updated on Oct 28 - Nov 03, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/41/</id>
    <title>Awesome Machine Learning Updates on Oct 14 - Oct 20, 2019</title>
    <updated>2019-10-07T17:09:17.000Z</updated>
    <published>2019-10-07T17:09:17.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/cortexlabs/cortex" rel="noopener noreferrer">Cortex (⭐8k)</a> - Open source platform for deploying machine learning models in production.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/41/"/>
    <summary>1 awesome projects updated on Oct 14 - Oct 20, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/40/</id>
    <title>Awesome Machine Learning Updates on Oct 07 - Oct 13, 2019</title>
    <updated>2019-10-06T17:57:29.000Z</updated>
    <published>2019-10-03T14:50:34.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/featuretools/featuretools" rel="noopener noreferrer">Featuretools (⭐7.6k)</a> - A library for automated feature engineering. It excels at transforming transactional and relational datasets into feature matrices for machine learning using reusable feature engineering "primitives".</li>
</ul>
<h3><p>Elixir / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/anshuman23/tensorflex" rel="noopener noreferrer">Tensorflex (⭐307)</a> - Tensorflow bindings for the Elixir programming language.</li>
</ul>
<h3><p>Go / Computer vision</p>
</h3>
<ul>
<li><a href="https://github.com/hybridgroup/gocv" rel="noopener noreferrer">GoCV (⭐7.4k)</a> - Package for computer vision using OpenCV 4 and beyond.</li>
</ul>
<h3><p>Data Analysis / Data Visualization / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://metacpan.org/pod/Paws::MachineLearning" rel="noopener noreferrer">Perl Data Language</a>,
a pluggable architecture for data and image processing, which can
be
<a href="https://github.com/zenogantner/PDL-ML" rel="noopener noreferrer">used for machine learning (⭐14)</a>.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/ProGamerGov/neural-style-pt" rel="noopener noreferrer">neural-style-pt (⭐860)</a> - A PyTorch implementation of Justin Johnson's neural-style (neural style transfer).</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/lancopku/pkuseg-python" rel="noopener noreferrer">pkuseg-python (⭐6.7k)</a> - A better version of Jieba, developed by Peking University.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/ClimbsRocks/auto_ml" rel="noopener noreferrer">auto_ml (⭐1.7k)</a> - Automated machine learning for production and analytics. Lets you focus on the fun parts of ML, while outputting production-ready code, and detailed analytics of your dataset and results. Includes support for NLP, XGBoost, CatBoost, LightGBM, and soon, deep learning.</li>
</ul>

<ul>
<li><a href="https://github.com/cogitare-ai/cogitare" rel="noopener noreferrer">Cogitare (⭐77)</a>: A Modern, Fast, and Modular Deep Learning and Machine Learning framework for Python.</li>
</ul>

<ul>
<li><a href="https://github.com/google/jax" rel="noopener noreferrer">JAX (⭐35k)</a> - JAX is Autograd and XLA, brought together for high-performance machine learning research.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/Yannael/BigDataAnalytics_INFOH515" rel="noopener noreferrer">Map/Reduce implementations of common ML algorithms (⭐62)</a>: Jupyter notebooks that cover how to implement from scratch different ML algorithms (ordinary least squares, gradient descent, k-means, alternating least squares), using Python NumPy, and how to then make these implementations scalable using Map/Reduce and Spark.</li>
</ul>
<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/SerpentAI/SerpentAI" rel="noopener noreferrer">Serpent.AI (⭐7k)</a> - Serpent.AI is a game agent framework that allows you to turn any video game you own into a sandbox to develop AI and machine learning experiments. For both researchers and hobbyists.</li>
</ul>
<h3><p>Swift / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/tensorflow/swift" rel="noopener noreferrer">Swift for Tensorflow (⭐6.1k)</a> - a next-generation platform for machine learning, incorporating the latest research across machine learning, compilers, differentiable programming, systems design, and beyond.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/40/"/>
    <summary>12 awesome projects updated on Oct 07 - Oct 13, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/38/</id>
    <title>Awesome Machine Learning Updates on Sep 23 - Sep 29, 2019</title>
    <updated>2019-09-19T02:07:30.000Z</updated>
    <published>2019-09-17T11:07:01.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / Demos and Scripts</p>
</h3>
<ul>
<li><a href="http://nsfwjs.com" rel="noopener noreferrer">NSFWJS</a> - Indecent content checker with TensorFlow.js</li>
</ul>

<ul>
<li><a href="https://rps-tfjs.netlify.com/" rel="noopener noreferrer">Rock Paper Scissors</a> - Rock Paper Scissors trained in the browser with TensorFlow.js</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/PreferredAI/cornac" rel="noopener noreferrer">Cornac (⭐1k)</a> - A comparative framework for multimodal recommender systems with a focus on models leveraging auxiliary data.</li>
</ul>
<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://www.manning.com/livevideo/machine-learning-data-science-and-deep-learning-with-python" rel="noopener noreferrer">Machine Learning, Data Science and Deep Learning with Python</a> - LiveVideo course that covers machine learning, Tensorflow, artificial intelligence, and neural networks.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/38/"/>
    <summary>4 awesome projects updated on Sep 23 - Sep 29, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/36/</id>
    <title>Awesome Machine Learning Updates on Sep 09 - Sep 15, 2019</title>
    <updated>2019-09-05T12:01:41.000Z</updated>
    <published>2019-09-05T12:01:41.000Z</published>
    <content type="html"><![CDATA[<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/ml-tooling/ml-workspace" rel="noopener noreferrer">ML Workspace (⭐3.5k)</a> - All-in-one web-based IDE for machine learning and data science. The workspace is deployed as a docker container and is preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch) and dev tools (e.g., Jupyter, VS Code).</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/36/"/>
    <summary>1 awesome projects updated on Sep 09 - Sep 15, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/35/</id>
    <title>Awesome Machine Learning Updates on Sep 02 - Sep 08, 2019</title>
    <updated>2019-08-31T18:20:42.000Z</updated>
    <published>2019-08-26T02:25:24.000Z</published>
    <content type="html"><![CDATA[<h3><p>Go / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/Lazin/go-ngram" rel="noopener noreferrer">go-ngram (⭐114)</a> - In-memory n-gram index with compression. <em>[Deprecated]</em></li>
</ul>

<ul>
<li><a href="https://github.com/Rookii/paicehusk" rel="noopener noreferrer">paicehusk (⭐29)</a> - Golang implementation of the Paice/Husk Stemming Algorithm. <em>[Deprecated]</em></li>
</ul>

<ul>
<li><a href="https://github.com/reiver/go-porterstemmer" rel="noopener noreferrer">go-porterstemmer (⭐192)</a> - A native Go clean room implementation of the Porter Stemming algorithm. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/rlouf/birdland" rel="noopener noreferrer">birdland (⭐46)</a> - A recommendation library in Go.</li>
</ul>

<ul>
<li><a href="https://github.com/dmitryikh/leaves" rel="noopener noreferrer">leaves (⭐474)</a> - A pure Go implementation of the prediction part of GBRTs, including XGBoost and LightGBM.</li>
</ul>

<ul>
<li><a href="https://github.com/znly/go-ml-transpiler" rel="noopener noreferrer">go-ml-transpiler</a> - An open source Go transpiler for machine learning models.</li>
</ul>

<ul>
<li><a href="https://github.com/sjwhitworth/golearn" rel="noopener noreferrer">golearn (⭐9.4k)</a> - Machine learning for Go.</li>
</ul>

<ul>
<li><a href="https://github.com/cdipaolo/goml" rel="noopener noreferrer">goml (⭐1.6k)</a> - Machine learning library written in pure Go.</li>
</ul>

<ul>
<li><a href="https://github.com/gorgonia/gorgonia" rel="noopener noreferrer">gorgonia (⭐5.9k)</a> - Deep learning in Go.</li>
</ul>

<ul>
<li><a href="https://github.com/therfoo/therfoo" rel="noopener noreferrer">therfoo (⭐18)</a> - An embedded deep learning library for Go.</li>
</ul>

<ul>
<li><a href="https://github.com/jinyeom/neat" rel="noopener noreferrer">neat (⭐73)</a> - Plug-and-play, parallel Go framework for NeuroEvolution of Augmenting Topologies (NEAT). <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/fxsjy/gonn" rel="noopener noreferrer">GoNN (⭐360)</a> - GoNN is an implementation of Neural Network in Go Language, which includes BPNN, RBF, PCN. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/sudachen/go-dnn" rel="noopener noreferrer">go-dnn (⭐8)</a> - Deep Neural Networks for Golang (powered by MXNet)</li>
</ul>
<h3><p>Go / Spatial analysis and geometry</p>
</h3>
<ul>
<li><a href="https://github.com/twpayne/go-geom" rel="noopener noreferrer">go-geom (⭐967)</a> - Go library to handle geometries.</li>
</ul>

<ul>
<li><a href="https://github.com/golang/geo" rel="noopener noreferrer">gogeo (⭐1.8k)</a> - Spherical geometry in Go.</li>
</ul>
<h3><p>Go / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/go-gota/gota" rel="noopener noreferrer">gota (⭐3.3k)</a> - Dataframes.</li>
</ul>

<ul>
<li><a href="https://godoc.org/gonum.org/v1/gonum/mat" rel="noopener noreferrer">gonum/mat</a> - A linear algebra package for Go.</li>
</ul>

<ul>
<li><a href="https://godoc.org/gonum.org/v1/gonum/optimize" rel="noopener noreferrer">gonum/optimize</a> - Implementations of optimization algorithms.</li>
</ul>

<ul>
<li><a href="https://godoc.org/gonum.org/v1/plot" rel="noopener noreferrer">gonum/plot</a> - A plotting library.</li>
</ul>

<ul>
<li><a href="https://godoc.org/gonum.org/v1/gonum/stat" rel="noopener noreferrer">gonum/stat</a> - A statistics library.</li>
</ul>

<ul>
<li><a href="https://github.com/arafatk/glot" rel="noopener noreferrer">glot (⭐406)</a> - Glot is a plotting library for Golang built on top of gnuplot.</li>
</ul>

<ul>
<li><a href="https://github.com/mmcloughlin/globe" rel="noopener noreferrer">globe (⭐1.6k)</a> - Globe wireframe visualization.</li>
</ul>

<ul>
<li><a href="https://godoc.org/gonum.org/v1/gonum/graph" rel="noopener noreferrer">gonum/graph</a> - General-purpose graph library.</li>
</ul>

<ul>
<li><a href="https://github.com/StepLg/go-graph" rel="noopener noreferrer">go-graph (⭐95)</a> - Graph library for Go/Golang language. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Neuraxio/Neuraxle" rel="noopener noreferrer">Neuraxle (⭐614)</a>: A framework providing the right abstractions to ease research, development, and deployment of your ML pipelines.</li>
</ul>
<h3><p>Credits / Misc</p>
</h3>
<ul>
<li>References for Go were mostly cut-and-pasted from <a href="https://github.com/gopherdata/resources/tree/master/tooling" rel="noopener noreferrer">gopherdata (⭐887)</a></li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/35/"/>
    <summary>26 awesome projects updated on Sep 02 - Sep 08, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/33/</id>
    <title>Awesome Machine Learning Updates on Aug 19 - Aug 25, 2019</title>
    <updated>2019-08-16T11:14:34.000Z</updated>
    <published>2019-08-16T11:14:34.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/bigartm/bigartm" rel="noopener noreferrer">BigARTM (⭐673)</a> - topic modelling platform.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/33/"/>
    <summary>1 awesome projects updated on Aug 19 - Aug 25, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/27/</id>
    <title>Awesome Machine Learning Updates on Jul 08 - Jul 14, 2019</title>
    <updated>2019-07-03T05:19:00.000Z</updated>
    <published>2019-07-03T05:19:00.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/maitbayev/the-elements-of-statistical-learning" rel="noopener noreferrer">the-elements-of-statistical-learning (⭐426)</a> - This repository contains Jupyter notebooks implementing the algorithms found in the book and summary of the textbook.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/27/"/>
    <summary>1 awesome projects updated on Jul 08 - Jul 14, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/24/</id>
    <title>Awesome Machine Learning Updates on Jun 17 - Jun 23, 2019</title>
    <updated>2019-06-12T01:49:11.000Z</updated>
    <published>2019-06-11T19:05:44.000Z</published>
    <content type="html"><![CDATA[<h3><p>Julia / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://fluxml.ai/" rel="noopener noreferrer">Flux</a> - Relax! Flux is the ML library that doesn't make you tensor</li>
</ul>
<h3><p>Julia / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/JuliaText/WordTokenizers.jl" rel="noopener noreferrer">Word Tokenizers (⭐100)</a> - Tokenizers for Natural Language Processing in Julia</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaText/CorpusLoaders.jl" rel="noopener noreferrer">Corpus Loaders (⭐32)</a> - A Julia package providing a variety of loaders for various NLP corpora.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaText/Embeddings.jl" rel="noopener noreferrer">Embeddings (⭐83)</a> - Functions and data dependencies for loading various word embeddings</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaText/Languages.jl" rel="noopener noreferrer">Languages (⭐57)</a> - Julia package for working with various human languages</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaText/WordNet.jl" rel="noopener noreferrer">WordNet (⭐35)</a> - A Julia package for Princeton's WordNet</li>
</ul>
<h3><p>Julia / Misc Stuff / Presentations</p>
</h3>
<ul>
<li><a href="https://github.com/oxinabox/DataDeps.jl" rel="noopener noreferrer">DataDeps (⭐159)</a> - Reproducible data setup for reproducible science.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/prodmodel/prodmodel" rel="noopener noreferrer">Prodmodel (⭐58)</a> - Build tool for data science pipelines.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/24/"/>
    <summary>8 awesome projects updated on Jun 17 - Jun 23, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/23/</id>
    <title>Awesome Machine Learning Updates on Jun 10 - Jun 16, 2019</title>
    <updated>2019-06-06T06:36:54.000Z</updated>
    <published>2019-06-03T10:13:33.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/microsoft/tensorwatch" rel="noopener noreferrer">TensorWatch (⭐3.5k)</a> - Debugging and visualization tool for machine learning and data science. It extensively leverages Jupyter Notebook to show real-time visualizations of data in running processes such as machine learning training.</li>
</ul>
<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/p-christ/nn_builder" rel="noopener noreferrer">nn_builder (⭐165)</a> - nn_builder is a python package that lets you build neural networks in 1 line</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/23/"/>
    <summary>2 awesome projects updated on Jun 10 - Jun 16, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/19/</id>
    <title>Awesome Machine Learning Updates on May 13 - May 19, 2019</title>
    <updated>2019-05-10T19:13:00.000Z</updated>
    <published>2019-05-10T19:13:00.000Z</published>
    <content type="html"><![CDATA[<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://cran.r-project.org/web/packages/spectralGraphTopology/index.html" rel="noopener noreferrer">spectralGraphTopology</a> - spectralGraphTopology: Learning Graphs from Data via Spectral Constraints.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/19/"/>
    <summary>1 awesome projects updated on May 13 - May 19, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/18/</id>
    <title>Awesome Machine Learning Updates on May 06 - May 12, 2019</title>
    <updated>2019-04-30T14:57:19.000Z</updated>
    <published>2019-04-30T14:57:19.000Z</published>
    <content type="html"><![CDATA[<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/eaplatanios/tensorflow_scala" rel="noopener noreferrer">TensorFlow Scala (⭐941)</a> - Strongly-typed Scala API for TensorFlow.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/18/"/>
    <summary>1 awesome projects updated on May 06 - May 12, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/17/</id>
    <title>Awesome Machine Learning Updates on Apr 29 - May 05, 2019</title>
    <updated>2019-04-22T22:49:58.000Z</updated>
    <published>2019-04-22T22:49:58.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/arthurpaulino/miraiml" rel="noopener noreferrer">MiraiML (⭐26)</a>: An asynchronous engine for continuous &amp; autonomous machine learning, built for real-time usage.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/17/"/>
    <summary>1 awesome projects updated on Apr 29 - May 05, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/16/</id>
    <title>Awesome Machine Learning Updates on Apr 22 - Apr 28, 2019</title>
    <updated>2019-04-18T19:44:49.000Z</updated>
    <published>2019-04-15T18:44:57.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/bentoml/bentoml" rel="noopener noreferrer">BentoML (⭐8.6k)</a>: Toolkit for package and deploy machine learning models for serving in production</li>
</ul>

<ul>
<li><a href="https://github.com/ddbourgin/numpy-ml" rel="noopener noreferrer">numpy-ML (⭐16k)</a>: Reference implementations of ML models written in numpy</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/16/"/>
    <summary>2 awesome projects updated on Apr 22 - Apr 28, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/13/</id>
    <title>Awesome Machine Learning Updates on Apr 01 - Apr 07, 2019</title>
    <updated>2019-03-27T06:50:02.000Z</updated>
    <published>2019-03-27T06:50:02.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/stellargraph/stellargraph" rel="noopener noreferrer">StellarGraph (⭐3.1k)</a>: Machine Learning on Graphs, a Python library for machine learning on graph-structured (network-structured) data.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/13/"/>
    <summary>1 awesome projects updated on Apr 01 - Apr 07, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/10/</id>
    <title>Awesome Machine Learning Updates on Mar 11 - Mar 17, 2019</title>
    <updated>2019-03-05T19:18:08.000Z</updated>
    <published>2019-03-05T19:18:08.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Microsoft/Recommenders" rel="noopener noreferrer">Microsoft Recommenders (⭐22k)</a>: Examples and best practices for building recommendation systems, provided as Jupyter notebooks. The repo contains some of the latest state of the art algorithms from Microsoft Research as well as from other companies and institutions.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/10/"/>
    <summary>1 awesome projects updated on Mar 11 - Mar 17, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/7/</id>
    <title>Awesome Machine Learning Updates on Feb 18 - Feb 24, 2019</title>
    <updated>2019-02-12T10:56:23.000Z</updated>
    <published>2019-02-12T10:56:23.000Z</published>
    <content type="html"><![CDATA[<h3><p>Scala / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/JohnSnowLabs/spark-nlp" rel="noopener noreferrer">Spark NLP (⭐4.1k)</a> - Natural language processing library built on top of Apache Spark ML to provide simple, performant, and accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/7/"/>
    <summary>1 awesome projects updated on Feb 18 - Feb 24, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/5/</id>
    <title>Awesome Machine Learning Updates on Feb 04 - Feb 10, 2019</title>
    <updated>2019-01-30T07:00:41.000Z</updated>
    <published>2019-01-30T07:00:41.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Xtra-Computing/thundergbm" rel="noopener noreferrer">ThunderGBM (⭐711)</a> - A fast library for GBDTs and Random Forests on GPUs.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/5/"/>
    <summary>1 awesome projects updated on Feb 04 - Feb 10, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/4/</id>
    <title>Awesome Machine Learning Updates on Jan 28 - Feb 03, 2019</title>
    <updated>2019-01-25T10:40:11.000Z</updated>
    <published>2019-01-21T18:04:50.000Z</published>
    <content type="html"><![CDATA[<h3><p>APL / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/mattcunningham/naive-apl" rel="noopener noreferrer">naive-apl (⭐24)</a> - Naive Bayesian Classifier implementation in APL. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>C / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/SeniorSA/hybrid-rs-trainner" rel="noopener noreferrer">Hybrid Recommender System (⭐16)</a> - A hybrid recommender system based upon scikit-learn algorithms. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>C++ / Computer Vision</p>
</h3>
<ul>
<li><a href="http://eblearn.sourceforge.net/" rel="noopener noreferrer">EBLearn</a> - Eblearn is an object-oriented C++ library that implements various machine learning models <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://opencv.org" rel="noopener noreferrer">OpenCV</a> - OpenCV has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.</li>
</ul>
<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/jkomiyama/banditlib" rel="noopener noreferrer">BanditLib (⭐140)</a> - A simple Multi-armed Bandit library. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/jolibrain/deepdetect" rel="noopener noreferrer">DeepDetect (⭐2.5k)</a> - A machine learning API and server written in C++11. It makes state of the art machine learning easy to work with and integrate into existing applications.</li>
</ul>

<ul>
<li><a href="http://igraph.org/" rel="noopener noreferrer">igraph</a> - General purpose graph library.</li>
</ul>

<ul>
<li><a href="https://github.com/srendle/libfm" rel="noopener noreferrer">libfm (⭐1.5k)</a> - A generic approach that allows to mimic most factorization models by feature engineering.</li>
</ul>

<ul>
<li><a href="https://www.mlpack.org/" rel="noopener noreferrer">mlpack</a> - A scalable C++ machine learning library.</li>
</ul>

<ul>
<li><a href="https://github.com/VowpalWabbit/vowpal_wabbit" rel="noopener noreferrer">Vowpal Wabbit (VW) (⭐8.7k)</a> - A fast out-of-core learning system.</li>
</ul>

<ul>
<li><a href="https://github.com/mosdeo/LKYDeepNN" rel="noopener noreferrer">LKYDeepNN (⭐50)</a> - A header-only C++11 Neural Network library. Low dependency, native traditional chinese document.</li>
</ul>

<ul>
<li><a href="https://github.com/polyaxon/polyaxon" rel="noopener noreferrer">Polyaxon (⭐3.7k)</a> - A platform for reproducible and scalable machine learning and deep learning.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/BVLC/caffe" rel="noopener noreferrer">Caffe (⭐35k)</a> - A deep learning framework developed with cleanliness, readability, and speed in mind.</li>
</ul>

<ul>
<li><a href="https://github.com/jeff1evesque/machine-learning" rel="noopener noreferrer">machine learning (⭐260)</a> - automated build consisting of a <a href="https://github.com/jeff1evesque/machine-learning#web-interface" rel="noopener noreferrer">web-interface (⭐260)</a>, and set of <a href="https://github.com/jeff1evesque/machine-learning#programmatic-interface" rel="noopener noreferrer">programmatic-interface (⭐260)</a> API, for support vector machines. Corresponding dataset(s) are stored into a SQL database, then generated model(s) used for prediction(s), are stored into a NoSQL datastore.</li>
</ul>

<ul>
<li><a href="https://scikit-learn.org/" rel="noopener noreferrer">scikit-learn</a> - A Python module for machine learning built on top of SciPy.</li>
</ul>

<ul>
<li><a href="https://github.com/metric-learn/metric-learn" rel="noopener noreferrer">metric-learn (⭐1.4k)</a> - A Python module for metric learning.</li>
</ul>

<ul>
<li><a href="https://www.astroml.org/" rel="noopener noreferrer">astroML</a> - Machine Learning and Data Mining for Astronomy.</li>
</ul>

<ul>
<li><a href="https://github.com/hannes-brt/hebel" rel="noopener noreferrer">hebel (⭐1.2k)</a> - GPU-Accelerated Deep Learning Library in Python. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/chainer/chainer" rel="noopener noreferrer">Chainer (⭐5.9k)</a> - Flexible neural network framework.</li>
</ul>

<ul>
<li><a href="https://facebook.github.io/prophet/" rel="noopener noreferrer">prophet</a> - Fast and automated time series forecasting framework by Facebook.</li>
</ul>

<ul>
<li><a href="https://github.com/ContinuumIO/topik" rel="noopener noreferrer">topik (⭐93)</a> - Topic modelling toolkit. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://surpriselib.com" rel="noopener noreferrer">Surprise</a> - A scikit for building and analyzing recommender systems.</li>
</ul>

<ul>
<li><a href="https://github.com/muricoca/crab" rel="noopener noreferrer">Crab (⭐1.2k)</a> - A flexible, fast recommender engine. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/pprett/bolt" rel="noopener noreferrer">Bolt (⭐87)</a> - Bolt Online Learning Toolbox. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/patvarilly/CoverTree" rel="noopener noreferrer">CoverTree (⭐31)</a> - Python implementation of cover trees, near-drop-in replacement for scipy.spatial.kdtree <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/perone/Pyevolve" rel="noopener noreferrer">Pyevolve (⭐316)</a> - Genetic algorithm framework. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/zueve/neurolab" rel="noopener noreferrer">neurolab (⭐167)</a></li>
</ul>

<ul>
<li><a href="https://github.com/HIPS/Spearmint" rel="noopener noreferrer">Spearmint (⭐1.6k)</a> - Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/abhik/pebl/" rel="noopener noreferrer">Pebl (⭐104)</a> - Python Environment for Bayesian Learning. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/jmschrei/pomegranate" rel="noopener noreferrer">pomegranate (⭐3.5k)</a> - Hidden Markov Models for Python, implemented in Cython for speed and efficiency.</li>
</ul>

<ul>
<li><a href="https://github.com/andersbll/deeppy" rel="noopener noreferrer">pydeep (⭐1.4k)</a> - Deep Learning In Python. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/EpistasisLab/tpot" rel="noopener noreferrer">TPOT (⭐10k)</a> - Tool that automatically creates and optimizes machine learning pipelines using genetic programming. Consider it your personal data science assistant, automating a tedious part of machine learning.</li>
</ul>

<ul>
<li><a href="https://orange.biolab.si/" rel="noopener noreferrer">Orange</a> - Open source data visualization and data analysis for novices and experts.</li>
</ul>

<ul>
<li><a href="https://github.com/luispedro/milk" rel="noopener noreferrer">milk (⭐602)</a> - Machine learning toolkit focused on supervised classification. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/yandex/rep" rel="noopener noreferrer">REP (⭐700)</a> - an IPython-based environment for conducting data-driven research in a consistent and reproducible way. REP is not trying to substitute scikit-learn, but extends it and provides better user experience. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/RGF-team/rgf" rel="noopener noreferrer">rgf_python (⭐383)</a> - Python bindings for Regularized Greedy Forest (Tree) Library.</li>
</ul>

<ul>
<li><a href="https://github.com/modAL-python/modAL" rel="noopener noreferrer">modAL (⭐2.3k)</a> - A modular active learning framework for Python, built on top of scikit-learn.</li>
</ul>

<ul>
<li><a href="https://github.com/apple/turicreate" rel="noopener noreferrer">Turi Create (⭐11k)</a> - Machine learning from Apple. Turi Create simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app.</li>
</ul>
<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/apache/incubator-mxnet" rel="noopener noreferrer">MXNet (⭐21k)</a> - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, JavaScript and more.</li>
</ul>

<ul>
<li><a href="https://optunity.readthedocs.io/en/latest/" rel="noopener noreferrer">Optunity</a> - A library dedicated to automated hyperparameter optimization with a simple, lightweight API to facilitate drop-in replacement of grid search. Optunity is written in Python but interfaces seamlessly to R.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/ahaz/index.html" rel="noopener noreferrer">ahaz</a> - ahaz: Regularization for semiparametric additive hazards regression. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/arules/index.html" rel="noopener noreferrer">arules</a> - arules: Mining Association Rules and Frequent Itemsets</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/bmrm/index.html" rel="noopener noreferrer">bmrm</a> - bmrm: Bundle Methods for Regularized Risk Minimization Package.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/Boruta/index.html" rel="noopener noreferrer">Boruta</a> - Boruta: A wrapper algorithm for all-relevant feature selection.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/bst/index.html" rel="noopener noreferrer">bst</a> - bst: Gradient Boosting.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/C50/index.html" rel="noopener noreferrer">C50</a> - C50: C5.0 Decision Trees and Rule-Based Models.</li>
</ul>

<ul>
<li><a href="https://topepo.github.io/caret/index.html" rel="noopener noreferrer">caret</a> - Classification and Regression Training: Unified interface to ~150 ML algorithms in R.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/caretEnsemble/index.html" rel="noopener noreferrer">caretEnsemble</a> - caretEnsemble: Framework for fitting multiple caret models as well as creating ensembles of such models. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://machinelearningmastery.com/" rel="noopener noreferrer">Clever Algorithms For Machine Learning</a></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/Cubist/index.html" rel="noopener noreferrer">Cubist</a> - Cubist: Rule- and Instance-Based Regression Modelling.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/e1071/index.html" rel="noopener noreferrer">e1071</a> - e1071: Misc Functions of the Department of Statistics (e1071), TU Wien</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/earth/index.html" rel="noopener noreferrer">earth</a> - earth: Multivariate Adaptive Regression Spline Models</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/elasticnet/index.html" rel="noopener noreferrer">elasticnet</a> - elasticnet: Elastic-Net for Sparse Estimation and Sparse PCA.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/ElemStatLearn/index.html" rel="noopener noreferrer">ElemStatLearn</a> - ElemStatLearn: Data sets, functions and examples from the book: "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/evtree/index.html" rel="noopener noreferrer">evtree</a> - evtree: Evolutionary Learning of Globally Optimal Trees.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/forecast/index.html" rel="noopener noreferrer">forecast</a> - forecast: Timeseries forecasting using ARIMA, ETS, STLM, TBATS, and neural network models.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/forecastHybrid/index.html" rel="noopener noreferrer">forecastHybrid</a> - forecastHybrid: Automatic ensemble and cross validation of ARIMA, ETS, STLM, TBATS, and neural network models from the "forecast" package.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/fpc/index.html" rel="noopener noreferrer">fpc</a> - fpc: Flexible procedures for clustering.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/frbs/index.html" rel="noopener noreferrer">frbs</a> - frbs: Fuzzy Rule-based Systems for Classification and Regression Tasks. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/GAMBoost/index.html" rel="noopener noreferrer">GAMBoost</a> - GAMBoost: Generalized linear and additive models by likelihood based boosting. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/gamboostLSS/index.html" rel="noopener noreferrer">gamboostLSS</a> - gamboostLSS: Boosting Methods for GAMLSS.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/gbm/index.html" rel="noopener noreferrer">gbm</a> - gbm: Generalized Boosted Regression Models.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/glmnet/index.html" rel="noopener noreferrer">glmnet</a> - glmnet: Lasso and elastic-net regularized generalized linear models.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/glmpath/index.html" rel="noopener noreferrer">glmpath</a> - glmpath: L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/GMMBoost/index.html" rel="noopener noreferrer">GMMBoost</a> - GMMBoost: Likelihood-based Boosting for Generalized mixed models. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/grplasso/index.html" rel="noopener noreferrer">grplasso</a> - grplasso: Fitting user specified models with Group Lasso penalty.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/grpreg/index.html" rel="noopener noreferrer">grpreg</a> - grpreg: Regularization paths for regression models with grouped covariates.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/h2o/index.html" rel="noopener noreferrer">h2o</a> - A framework for fast, parallel, and distributed machine learning algorithms at scale -- Deeplearning, Random forests, GBM, KMeans, PCA, GLM.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/hda/index.html" rel="noopener noreferrer">hda</a> - hda: Heteroscedastic Discriminant Analysis. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://www-bcf.usc.edu/~gareth/ISL/" rel="noopener noreferrer">Introduction to Statistical Learning</a></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/ipred/index.html" rel="noopener noreferrer">ipred</a> - ipred: Improved Predictors.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/kernlab/index.html" rel="noopener noreferrer">kernlab</a> - kernlab: Kernel-based Machine Learning Lab.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/klaR/index.html" rel="noopener noreferrer">klaR</a> - klaR: Classification and visualization.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/lars/index.html" rel="noopener noreferrer">lars</a> - lars: Least Angle Regression, Lasso and Forward Stagewise. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/lasso2/index.html" rel="noopener noreferrer">lasso2</a> - lasso2: L1 constrained estimation aka ‘lasso’.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/LiblineaR/index.html" rel="noopener noreferrer">LiblineaR</a> - LiblineaR: Linear Predictive Models Based On The Liblinear C/C++ Library.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/LogicReg/index.html" rel="noopener noreferrer">LogicReg</a> - LogicReg: Logic Regression.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/maptree/index.html" rel="noopener noreferrer">maptree</a> - maptree: Mapping, pruning, and graphing tree models. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/mboost/index.html" rel="noopener noreferrer">mboost</a> - mboost: Model-Based Boosting.</li>
</ul>

<ul>
<li><a href="https://www.kaggle.com/general/3661" rel="noopener noreferrer">medley</a> - medley: Blending regression models, using a greedy stepwise approach.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/mlr/index.html" rel="noopener noreferrer">mlr</a> - mlr: Machine Learning in R.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/ncvreg/index.html" rel="noopener noreferrer">ncvreg</a> - ncvreg: Regularization paths for SCAD- and MCP-penalized regression models.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/nnet/index.html" rel="noopener noreferrer">nnet</a> - nnet: Feed-forward Neural Networks and Multinomial Log-Linear Models. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/pamr/index.html" rel="noopener noreferrer">pamr</a> - pamr: Pam: prediction analysis for microarrays. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/penalized/index.html" rel="noopener noreferrer">penalized</a> - penalized: L1 (lasso and fused lasso) and L2 (ridge) penalized estimation in GLMs and in the Cox model.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/penalizedLDA/index.html" rel="noopener noreferrer">penalizedLDA</a> - penalizedLDA: Penalized classification using Fisher's linear discriminant. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/penalizedSVM/index.html" rel="noopener noreferrer">penalizedSVM</a> - penalizedSVM: Feature Selection SVM using penalty functions.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/quantregForest/index.html" rel="noopener noreferrer">quantregForest</a> - quantregForest: Quantile Regression Forests.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/randomForest/index.html" rel="noopener noreferrer">randomForest</a> - randomForest: Breiman and Cutler's random forests for classification and regression.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/randomForestSRC/index.html" rel="noopener noreferrer">randomForestSRC</a> - randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/rattle/index.html" rel="noopener noreferrer">rattle</a> - rattle: Graphical user interface for data mining in R.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/rda/index.html" rel="noopener noreferrer">rda</a> - rda: Shrunken Centroids Regularized Discriminant Analysis.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/rdetools/index.html" rel="noopener noreferrer">rdetools</a> - rdetools: Relevant Dimension Estimation (RDE) in Feature Spaces. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/REEMtree/index.html" rel="noopener noreferrer">REEMtree</a> - REEMtree: Regression Trees with Random Effects for Longitudinal (Panel) Data. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/relaxo/index.html" rel="noopener noreferrer">relaxo</a> - relaxo: Relaxed Lasso. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/rgenoud/index.html" rel="noopener noreferrer">rgenoud</a> - rgenoud: R version of GENetic Optimization Using Derivatives</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/Rmalschains/index.html" rel="noopener noreferrer">Rmalschains</a> - Rmalschains: Continuous Optimization using Memetic Algorithms with Local Search Chains (MA-LS-Chains) in R.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/rminer/index.html" rel="noopener noreferrer">rminer</a> - rminer: Simpler use of data mining methods (e.g. NN and SVM) in classification and regression. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/ROCR/index.html" rel="noopener noreferrer">ROCR</a> - ROCR: Visualizing the performance of scoring classifiers. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/RoughSets/index.html" rel="noopener noreferrer">RoughSets</a> - RoughSets: Data Analysis Using Rough Set and Fuzzy Rough Set Theories. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/rpart/index.html" rel="noopener noreferrer">rpart</a> - rpart: Recursive Partitioning and Regression Trees.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/RPMM/index.html" rel="noopener noreferrer">RPMM</a> - RPMM: Recursively Partitioned Mixture Model.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/RSNNS/index.html" rel="noopener noreferrer">RSNNS</a> - RSNNS: Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS).</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/RWeka/index.html" rel="noopener noreferrer">RWeka</a> - RWeka: R/Weka interface.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/RXshrink/index.html" rel="noopener noreferrer">RXshrink</a> - RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least Angle Regression.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/sda/index.html" rel="noopener noreferrer">sda</a> - sda: Shrinkage Discriminant Analysis and CAT Score Variable Selection. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/ecpolley/SuperLearner" rel="noopener noreferrer">SuperLearner (⭐290)</a> - Multi-algorithm ensemble learning packages.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/svmpath/index.html" rel="noopener noreferrer">svmpath</a> - svmpath: svmpath: the SVM Path algorithm. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/tgp/index.html" rel="noopener noreferrer">tgp</a> - tgp: Bayesian treed Gaussian process models. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/tree/index.html" rel="noopener noreferrer">tree</a> - tree: Classification and regression trees.</li>
</ul>

<ul>
<li><a href="https://cran.r-project.org/web/packages/varSelRF/index.html" rel="noopener noreferrer">varSelRF</a> - varSelRF: Variable selection using random forests.</li>
</ul>

<ul>
<li><a href="https://igraph.org/r/" rel="noopener noreferrer">igraph</a> - binding to igraph library - General purpose graph library.</li>
</ul>
<h3><p>Matlab / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Xtra-Computing/thundersvm" rel="noopener noreferrer">ThunderSVM (⭐1.6k)</a> - An Open-Source SVM Library on GPUs and CPUs</li>
</ul>

<ul>
<li><a href="https://www.socher.org/index.php/Main/Convolutional-RecursiveDeepLearningFor3DObjectClassification" rel="noopener noreferrer">Convolutional-Recursive Deep Learning for 3D Object Classification</a> - Convolutional-Recursive Deep Learning for 3D Object Classification[DEEP LEARNING].</li>
</ul>

<ul>
<li><a href="https://people.kyb.tuebingen.mpg.de/spider/" rel="noopener noreferrer">Spider</a> - The spider is intended to be a complete object orientated environment for machine learning in Matlab.</li>
</ul>

<ul>
<li><a href="https://www.csie.ntu.edu.tw/~cjlin/libsvm/#matlab" rel="noopener noreferrer">LibSVM</a> - A Library for Support Vector Machines.</li>
</ul>

<ul>
<li><a href="https://www.csie.ntu.edu.tw/~cjlin/liblinear/#download" rel="noopener noreferrer">LibLinear</a> - A Library for Large Linear Classification.</li>
</ul>

<ul>
<li><a href="https://github.com/covartech/PRT" rel="noopener noreferrer">Pattern Recognition Toolbox (⭐145)</a> - A complete object-oriented environment for machine learning in Matlab.</li>
</ul>
<h3><p>C++ / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://taku910.github.io/crfpp/" rel="noopener noreferrer">CRF++</a> - Open source implementation of Conditional Random Fields (CRFs) for segmenting/labeling sequential data &amp; other Natural Language Processing tasks. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="http://www.chokkan.org/software/crfsuite/" rel="noopener noreferrer">CRFsuite</a> - CRFsuite is an implementation of Conditional Random Fields (CRFs) for labeling sequential data. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/LanguageMachines/libfolia" rel="noopener noreferrer">libfolia (⭐17)</a> - C++ library for the <a href="https://proycon.github.io/folia/" rel="noopener noreferrer">FoLiA format</a></li>
</ul>
<h3><p>Common Lisp / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/melisgl/mgl/" rel="noopener noreferrer">mgl (⭐643)</a> - Neural networks (boltzmann machines, feed-forward and recurrent nets), Gaussian Processes.</li>
</ul>

<ul>
<li><a href="https://github.com/melisgl/mgl-gpr/" rel="noopener noreferrer">mgl-gpr (⭐66)</a> - Evolutionary algorithms. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/melisgl/cl-libsvm/" rel="noopener noreferrer">cl-libsvm (⭐16)</a> - Wrapper for the libsvm support vector machine library. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Clojure / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/lspector/Clojush" rel="noopener noreferrer">Clojush (⭐337)</a> - The Push programming language and the PushGP genetic programming system implemented in Clojure.</li>
</ul>

<ul>
<li><a href="https://github.com/jimpil/enclog" rel="noopener noreferrer">Encog (⭐136)</a> - Clojure wrapper for Encog (v3) (Machine-Learning framework that specializes in neural-nets). <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/vollmerm/fungp" rel="noopener noreferrer">Fungp (⭐100)</a> - A genetic programming library for Clojure. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/clojurewerkz/statistiker" rel="noopener noreferrer">Statistiker (⭐64)</a> - Basic Machine Learning algorithms in Clojure. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/htm-community/clortex" rel="noopener noreferrer">clortex (⭐182)</a> - General Machine Learning library using Numenta’s Cortical Learning Algorithm. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/htm-community/comportex" rel="noopener noreferrer">comportex (⭐153)</a> - Functionally composable Machine Learning library using Numenta’s Cortical Learning Algorithm. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Clojure / Deep Learning</p>
</h3>
<ul>
<li><a href="https://github.com/originrose/cortex" rel="noopener noreferrer">cortex (⭐1.3k)</a> - Neural networks, regression and feature learning in Clojure.</li>
</ul>
<h3><p>Crystal / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/NeuraLegion/crystal-fann" rel="noopener noreferrer">crystal-fann (⭐87)</a> - FANN (Fast Artificial Neural Network) binding.</li>
</ul>
<h3><p>Erlang / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/discoproject/disco/" rel="noopener noreferrer">Disco (⭐1.6k)</a> - Map Reduce in Erlang. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/daviddengcn/go-pr" rel="noopener noreferrer">go-pr (⭐68)</a> - Pattern recognition package in Go lang. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/alonsovidales/go_ml" rel="noopener noreferrer">go-ml (⭐199)</a> - Linear / Logistic regression, Neural Networks, Collaborative Filtering and Gaussian Multivariate Distribution. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/jbrukh/bayesian" rel="noopener noreferrer">bayesian (⭐812)</a> - Naive Bayesian Classification for Golang. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/thoj/go-galib" rel="noopener noreferrer">go-galib (⭐202)</a> - Genetic Algorithms library written in Go / Golang. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/ryanbressler/CloudForest" rel="noopener noreferrer">Cloudforest (⭐748)</a> - Ensembles of decision trees in Go/Golang. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Go / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/ajstarks/svgo" rel="noopener noreferrer">SVGo (⭐2.2k)</a> - The Go Language library for SVG generation.</li>
</ul>

<ul>
<li><a href="https://github.com/fxsjy/RF.go" rel="noopener noreferrer">RF (⭐115)</a> - Random forests implementation in Go. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Haskell / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/ajtulloch/haskell-ml" rel="noopener noreferrer">haskell-ml (⭐60)</a> - Haskell implementations of various ML algorithms. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/mikeizbicki/HLearn" rel="noopener noreferrer">HLearn (⭐1.7k)</a> - a suite of libraries for interpreting machine learning models according to their algebraic structure. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/alpmestan/HNN" rel="noopener noreferrer">hnn (⭐114)</a> - Haskell Neural Network library.</li>
</ul>

<ul>
<li><a href="https://github.com/ajtulloch/hopfield-networks" rel="noopener noreferrer">hopfield-networks (⭐16)</a> - Hopfield Networks for unsupervised learning in Haskell. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/ajtulloch/dnngraph" rel="noopener noreferrer">DNNGraph (⭐711)</a> - A DSL for deep neural networks. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/jbarrow/LambdaNet" rel="noopener noreferrer">LambdaNet (⭐383)</a> - Configurable Neural Networks in Haskell. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Java / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://www.cortical.io/" rel="noopener noreferrer">Cortical.io</a> - Retina: an API performing complex NLP operations (disambiguation, classification, streaming text filtering, etc...) as quickly and intuitively as the brain.</li>
</ul>

<ul>
<li><a href="https://github.com/cortical-io/Iris" rel="noopener noreferrer">IRIS</a> - <a href="https://cortical.io" rel="noopener noreferrer">Cortical.io's</a> FREE NLP, Retina API Analysis Tool (written in JavaFX!) - <a href="https://www.youtube.com/watch?v=CsF4pd7fGF0" rel="noopener noreferrer">See the Tutorial Video</a>.</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/corenlp.shtml" rel="noopener noreferrer">CoreNLP</a> - Stanford CoreNLP provides a set of natural language analysis tools which can take raw English language text input and give the base forms of words.</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/lex-parser.shtml" rel="noopener noreferrer">Stanford Parser</a> - A natural language parser is a program that works out the grammatical structure of sentences.</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/tagger.shtml" rel="noopener noreferrer">Stanford POS Tagger</a> - A Part-Of-Speech Tagger (POS Tagger).</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/CRF-NER.shtml" rel="noopener noreferrer">Stanford Name Entity Recognizer</a> - Stanford NER is a Java implementation of a Named Entity Recognizer.</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/segmenter.shtml" rel="noopener noreferrer">Stanford Word Segmenter</a> - Tokenization of raw text is a standard pre-processing step for many NLP tasks.</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/tregex.shtml" rel="noopener noreferrer">Tregex, Tsurgeon and Semgrex</a> - Tregex is a utility for matching patterns in trees, based on tree relationships and regular expression matches on nodes (the name is short for "tree regular expressions").</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/phrasal/" rel="noopener noreferrer">Stanford Phrasal: A Phrase-Based Translation System</a></li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/tokenizer.shtml" rel="noopener noreferrer">Stanford English Tokenizer</a> - Stanford Phrasal is a state-of-the-art statistical phrase-based machine translation system, written in Java.</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/tokensregex.shtml" rel="noopener noreferrer">Stanford Tokens Regex</a> - A tokenizer divides text into a sequence of tokens, which roughly correspond to "words".</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/sutime.shtml" rel="noopener noreferrer">Stanford Temporal Tagger</a> - SUTime is a library for recognizing and normalizing time expressions.</li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/patternslearning.shtml" rel="noopener noreferrer">Stanford SPIED</a> - Learning entities from unlabeled text starting with seed sets using patterns in an iterative fashion.</li>
</ul>

<ul>
<li><a href="https://github.com/twitter/twitter-text/tree/master/java" rel="noopener noreferrer">Twitter Text Java (⭐3.1k)</a> - A Java implementation of Twitter's text processing library.</li>
</ul>

<ul>
<li><a href="https://github.com/ClearTK/cleartk" rel="noopener noreferrer">ClearTK (⭐133)</a> - ClearTK provides a framework for developing statistical natural language processing (NLP) components in Java and is built on top of Apache UIMA. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/emorynlp/nlp4j" rel="noopener noreferrer">NLP4J (⭐156)</a> - The NLP4J project provides software and resources for natural language processing. The project started at the Center for Computational Language and EducAtion Research, and is currently developed by the Center for Language and Information Research at Emory University. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/CogComp/cogcomp-nlp" rel="noopener noreferrer">CogcompNLP (⭐480)</a> - This project collects a number of core libraries for Natural Language Processing (NLP) developed in the University of Illinois' Cognitive Computation Group, for example <code>illinois-core-utilities</code> which provides a set of NLP-friendly data structures and a number of NLP-related utilities that support writing NLP applications, running experiments, etc, <code>illinois-edison</code> a library for feature extraction from illinois-core-utilities data structures and many other packages.</li>
</ul>
<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://ci.apache.org/projects/flink/flink-docs-master/dev/libs/ml/index.html" rel="noopener noreferrer">FlinkML in Apache Flink</a> - Distributed machine learning library in Flink.</li>
</ul>

<ul>
<li><a href="https://deeplearning.thoughtworks.school/" rel="noopener noreferrer">DeepLearning.scala</a> - Creating statically typed dynamic neural networks from object-oriented &amp; functional programming constructs.</li>
</ul>

<ul>
<li><a href="https://github.com/tresata/ganitha" rel="noopener noreferrer">ganitha (⭐109)</a> - Scalding powered machine learning. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/CogComp/saul" rel="noopener noreferrer">Saul (⭐63)</a> - Flexible Declarative Learning-Based Programming.</li>
</ul>
<h3><p>Scala / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://spark.apache.org/docs/latest/mllib-guide.html" rel="noopener noreferrer">MLlib in Apache Spark</a> - Distributed machine learning library in Spark</li>
</ul>

<ul>
<li><a href="https://flink.apache.org/" rel="noopener noreferrer">Flink</a> - Open source platform for distributed stream and batch data processing.</li>
</ul>

<ul>
<li><a href="https://github.com/xerial/xerial" rel="noopener noreferrer">xerial (⭐19)</a> - Data management utilities for Scala. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/apache/predictionio" rel="noopener noreferrer">PredictionIO (⭐13k)</a> - PredictionIO, a machine learning server for software developers and data engineers.</li>
</ul>
<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://sourceforge.net/p/lemur/wiki/RankLib/" rel="noopener noreferrer">RankLib</a> - RankLib is a library of learning to rank algorithms. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://nlp.stanford.edu/software/classifier.shtml" rel="noopener noreferrer">Stanford Classifier</a> - A classifier is a machine learning tool that will take data items and place them into one of k classes.</li>
</ul>

<ul>
<li><a href="https://github.com/apache/systemml" rel="noopener noreferrer">SystemML (⭐1.1k)</a> - flexible, scalable machine learning (ML) language.</li>
</ul>

<ul>
<li><a href="https://www.cs.waikato.ac.nz/ml/weka/" rel="noopener noreferrer">Weka</a> - Weka is a collection of machine learning algorithms for data mining tasks.</li>
</ul>

<ul>
<li><a href="https://github.com/CogComp/lbjava" rel="noopener noreferrer">LBJava (⭐14)</a> - Learning Based Java is a modelling language for the rapid development of software systems, offers a convenient, declarative syntax for classifier and constraint definition directly in terms of the objects in the programmer's application.</li>
</ul>
<h3><p>Java / Speech Recognition</p>
</h3>
<ul>
<li><a href="https://cmusphinx.github.io" rel="noopener noreferrer">CMU Sphinx</a> - Open Source Toolkit For Speech Recognition purely based on Java speech recognition library.</li>
</ul>
<h3><p>Java / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/apache/hadoop" rel="noopener noreferrer">Hadoop (⭐16k)</a> - Hadoop/HDFS.</li>
</ul>

<ul>
<li><a href="https://storm.apache.org/" rel="noopener noreferrer">Storm</a> - Storm is a distributed realtime computation system.</li>
</ul>

<ul>
<li><a href="https://jwork.org/dmelt/" rel="noopener noreferrer">DataMelt</a> - Mathematics software for numeric computation, statistics, symbolic calculations, data analysis and data visualization.</li>
</ul>
<h3><p>JavaScript / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/retextjs/retext" rel="noopener noreferrer">Retext (⭐2.4k)</a> - Extensible system for analyzing and manipulating natural language.</li>
</ul>

<ul>
<li><a href="https://github.com/spencermountain/compromise" rel="noopener noreferrer">NLP Compromise (⭐12k)</a> - Natural Language processing in the browser.</li>
</ul>
<h3><p>JavaScript / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.highcharts.com/" rel="noopener noreferrer">High Charts</a></li>
</ul>

<ul>
<li><a href="https://dc-js.github.io/dc.js/" rel="noopener noreferrer">dc.js</a></li>
</ul>

<ul>
<li><a href="https://www.chartjs.org/" rel="noopener noreferrer">chartjs</a></li>
</ul>

<ul>
<li><a href="https://github.com/NathanEpstein/D3xter" rel="noopener noreferrer">D3xter (⭐336)</a> - Straight forward plotting built on D3. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/rigtorp/statkit" rel="noopener noreferrer">statkit (⭐50)</a> - Statistics kit for JavaScript. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/jasondavies/science.js/" rel="noopener noreferrer">science.js (⭐894)</a> - Scientific and statistical computing in JavaScript. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/NathanEpstein/Z3d" rel="noopener noreferrer">Z3d (⭐88)</a> - Easily make interactive 3d plots built on Three.js <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://c3js.org/" rel="noopener noreferrer">C3.js</a> - customizable library based on D3.js for easy chart drawing.</li>
</ul>

<ul>
<li><a href="https://datamaps.github.io/" rel="noopener noreferrer">Datamaps</a> - Customizable SVG map/geo visualizations using D3.js. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://www.zingchart.com/" rel="noopener noreferrer">ZingChart</a> - library written on Vanilla JS for big data visualization.</li>
</ul>

<ul>
<li><a href="https://www.cheminfo.org/" rel="noopener noreferrer">cheminfo</a> - Platform for data visualization and analysis, using the <a href="https://github.com/npellet/visualizer" rel="noopener noreferrer">visualizer (⭐51)</a> project.</li>
</ul>

<ul>
<li><a href="https://www.anychart.com/" rel="noopener noreferrer">AnyChart</a></li>
</ul>

<ul>
<li><a href="https://www.fusioncharts.com/" rel="noopener noreferrer">FusionCharts</a></li>
</ul>

<ul>
<li><a href="https://nivo.rocks" rel="noopener noreferrer">Nivo</a> - built on top of the awesome d3 and Reactjs libraries</li>
</ul>
<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://cs.stanford.edu/people/karpathy/convnetjs/" rel="noopener noreferrer">Convnet.js</a> - ConvNetJS is a JavaScript library for training Deep Learning models[DEEP LEARNING] <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://harthur.github.io/clusterfck/" rel="noopener noreferrer">Clusterfck</a> - Agglomerative hierarchical clustering implemented in JavaScript for Node.js and the browser. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/emilbayes/clustering.js" rel="noopener noreferrer">Clustering.js (⭐30)</a> - Clustering algorithms implemented in JavaScript for Node.js and the browser. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/serendipious/nodejs-decision-tree-id3" rel="noopener noreferrer">Decision Trees (⭐220)</a> - NodeJS Implementation of Decision Tree using ID3 Algorithm. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/antoniodeluca/dn2a.js" rel="noopener noreferrer">DN2A (⭐465)</a> - Digital Neural Networks Architecture. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/rlidwka/node-fann" rel="noopener noreferrer">Node-fann (⭐183)</a> - FANN (Fast Artificial Neural Network Library) bindings for Node.js <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/emilbayes/kMeans.js" rel="noopener noreferrer">Kmeans.js (⭐46)</a> - Simple JavaScript implementation of the k-means algorithm, for node.js and the browser. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/yandongliu/learningjs" rel="noopener noreferrer">Learning.js (⭐65)</a> - JavaScript implementation of logistic regression/c4.5 decision tree <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/machinelearnjs/machinelearnjs" rel="noopener noreferrer">machinelearn.js (⭐541)</a> - Machine Learning library for the web, Node.js and developers</li>
</ul>

<ul>
<li><a href="https://github.com/BrainJS/brain.js" rel="noopener noreferrer">Brain.js (⭐15k)</a> - Neural networks in JavaScript - continued community fork of <a href="https://github.com/harthur/brain" rel="noopener noreferrer">Brain (⭐8k)</a>.</li>
</ul>

<ul>
<li><a href="https://github.com/omphalos/bayesian-bandit.js" rel="noopener noreferrer">Bayesian-Bandit (⭐45)</a> - Bayesian bandit implementation for Node and the browser. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/totemstech/neuraln" rel="noopener noreferrer">NeuralN (⭐274)</a> - C++ Neural Network library for Node.js. It has advantage on large dataset and multi-threaded training. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/itamarwe/kalman" rel="noopener noreferrer">kalman (⭐114)</a> - Kalman filter for JavaScript. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/luccastera/shaman" rel="noopener noreferrer">shaman (⭐106)</a> - Node.js library with support for both simple and multiple linear regression. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>JavaScript / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/jcoglan/sylvester" rel="noopener noreferrer">sylvester (⭐1.2k)</a> - Vector and Matrix math for JavaScript. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/flurry/Lyric" rel="noopener noreferrer">Lyric (⭐42)</a> - Linear Regression library. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Julia / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/benhamner/MachineLearning.jl" rel="noopener noreferrer">MachineLearning (⭐119)</a> - Julia Machine Learning library. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/lindahua/Regression.jl" rel="noopener noreferrer">Regression (⭐64)</a> - Algorithms for regression analysis (e.g. linear regression and logistic regression). <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/Loess.jl" rel="noopener noreferrer">Local Regression (⭐110)</a> - Local regression, so smooooth!</li>
</ul>

<ul>
<li><a href="https://github.com/nutsiepully/NaiveBayes.jl" rel="noopener noreferrer">Naive Bayes (⭐8)</a> - Simple Naive Bayes implementation in Julia. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/fredo-dedup/SimpleMCMC.jl" rel="noopener noreferrer">Simple MCMC (⭐12)</a> - basic MCMC sampler implemented in Julia. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/Distances.jl" rel="noopener noreferrer">Distances (⭐471)</a> - Julia module for Distance evaluation.</li>
</ul>

<ul>
<li><a href="https://github.com/doobwa/MCMC.jl" rel="noopener noreferrer">MCMC (⭐36)</a> - MCMC tools for Julia. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/lendle/OnlineLearning.jl" rel="noopener noreferrer">Online Learning (⭐14)</a> <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/MultivariateStats.jl" rel="noopener noreferrer">MultivariateStats (⭐386)</a> - Methods for dimensionality reduction.</li>
</ul>

<ul>
<li><a href="https://github.com/EricChiang/ANN.jl" rel="noopener noreferrer">ANN (⭐55)</a> - Julia artificial neural networks. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/pluskid/Mocha.jl" rel="noopener noreferrer">Mocha (⭐1.3k)</a> - Deep Learning framework for Julia inspired by Caffe. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Julia / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/slycoder/TopicModels.jl" rel="noopener noreferrer">Topic Models (⭐38)</a> - TopicModels for Julia. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/JuliaText/TextAnalysis.jl" rel="noopener noreferrer">Text Analysis (⭐382)</a> - Julia package for text analysis.</li>
</ul>
<h3><p>Julia / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/JuliaData/DataFramesMeta.jl" rel="noopener noreferrer">Data Frames Meta (⭐497)</a> - Metaprogramming tools for DataFrames.</li>
</ul>

<ul>
<li><a href="https://github.com/nfoti/JuliaData" rel="noopener noreferrer">Julia Data (⭐6)</a> - library for working with tabular data in Julia. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/queryverse/ReadStat.jl" rel="noopener noreferrer">Data Read (⭐80)</a> - Read files from Stata, SAS, and SPSS.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/StatsKit.jl" rel="noopener noreferrer">Stats (⭐143)</a> - Statistical tests for Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaData/DataFrames.jl" rel="noopener noreferrer">DataFrames (⭐1.8k)</a> - library for working with tabular data in Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/DataArrays.jl" rel="noopener noreferrer">Data Arrays (⭐53)</a> - Data structures that allow missing values. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Julia / Misc Stuff / Presentations</p>
</h3>
<ul>
<li><a href="https://github.com/JuliaDSP/DSP.jl" rel="noopener noreferrer">SignalProcessing (⭐416)</a> - Signal Processing tools for Julia.</li>
</ul>
<h3><p>Lua / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://labix.org/lunatic-python" rel="noopener noreferrer">Lunatic Python</a></li>
</ul>

<ul>
<li><a href="https://bitbucket.org/lucashnegri/lna" rel="noopener noreferrer">Lua - Numerical Algorithms</a> <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/jzrake/lunum" rel="noopener noreferrer">Lunum (⭐40)</a> <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Matlab / Computer Vision</p>
</h3>
<ul>
<li><a href="https://www3.math.tu-berlin.de/numerik/www.shearlab.org/software" rel="noopener noreferrer">Shearlets</a> - MATLAB code for shearlet transform.</li>
</ul>

<ul>
<li><a href="https://kyamagu.github.io/mexopencv/" rel="noopener noreferrer">mexopencv</a> - Collection and a development kit of MATLAB mex functions for OpenCV library.</li>
</ul>
<h3><p>Matlab / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.cs.purdue.edu/homes/dgleich/packages/matlab_bgl/" rel="noopener noreferrer">matlab_bgl</a> - MatlabBGL is a Matlab package for working with graphs.</li>
</ul>

<ul>
<li><a href="https://www.mathworks.com/matlabcentral/fileexchange/24134-gaimc---graph-algorithms-in-matlab-code" rel="noopener noreferrer">gaimc</a> - Efficient pure-Matlab implementations of graph algorithms to complement MatlabBGL's mex functions.</li>
</ul>
<h3><p>.NET / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://www.nuget.org/packages/Accord.MachineLearning/" rel="noopener noreferrer">Accord.MachineLearning</a> - Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. This package is part of the Accord.NET Framework.</li>
</ul>

<ul>
<li><a href="https://diffsharp.github.io/DiffSharp/" rel="noopener noreferrer">DiffSharp</a> - An automatic differentiation (AD) library providing exact and efficient derivatives (gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products) for machine learning and optimization applications. Operations can be nested to any level, meaning that you can compute exact higher-order derivatives and differentiate functions that are internally making use of differentiation, for applications such as hyperparameter optimization.</li>
</ul>

<ul>
<li><a href="https://www.nuget.org/packages/encog-dotnet-core/" rel="noopener noreferrer">Encog</a> - An advanced neural network and machine learning framework. Encog contains classes to create a wide variety of networks, as well as support classes to normalize and process data for these neural networks. Encog trains using multithreaded resilient propagation. Encog can also make use of a GPU to further speed processing time. A GUI based workbench is also provided to help model and train neural networks.</li>
</ul>
<h3><p>.NET / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.nuget.org/packages/numl/" rel="noopener noreferrer">numl</a> - numl is a machine learning library intended to ease the use of using standard modelling techniques for both prediction and clustering.</li>
</ul>

<ul>
<li><a href="https://www.microsoft.com/en-us/research/project/sho-the-net-playground-for-data/" rel="noopener noreferrer">Sho</a> - Sho is an interactive environment for data analysis and scientific computing that lets you seamlessly connect scripts (in IronPython) with compiled code (in .NET) to enable fast and flexible prototyping. The environment includes powerful and efficient libraries for linear algebra as well as data visualization that can be used from any .NET language, as well as a feature-rich interactive shell for rapid development.</li>
</ul>
<h3><p>General-Purpose Machine Learning / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/Kalvar/ios-KRFuzzyCMeans-Algorithm" rel="noopener noreferrer">KRFuzzyCMeans-Algorithm (⭐12)</a> - It implemented Fuzzy C-Means (FCM) the fuzzy clustering / classification algorithm on Machine Learning. It could be used in data mining and image compression. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/rleonid/oml" rel="noopener noreferrer">Oml (⭐119)</a> - A general statistics and machine learning library.</li>
</ul>

<ul>
<li><a href="https://mmottl.github.io/gpr/" rel="noopener noreferrer">GPR</a> - Efficient Gaussian Process Regression in OCaml.</li>
</ul>

<ul>
<li><a href="https://libra.cs.uoregon.edu" rel="noopener noreferrer">Libra-Tk</a> - Algorithms for learning and inference with discrete probabilistic models.</li>
</ul>

<ul>
<li><a href="https://metacpan.org/pod/Algorithm::SVMLight" rel="noopener noreferrer">Algorithm::SVMLight</a>,
implementation of Support Vector Machines with SVMLight under it. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li>Several machine learning and artificial intelligence models are
included in the <a href="https://metacpan.org/search?size=20&amp;q=AI" rel="noopener noreferrer"><code>AI</code></a>
namespace. For instance, you can
find <a href="https://metacpan.org/pod/AI::NaiveBayes" rel="noopener noreferrer">Naïve Bayes</a>.</li>
</ul>
<h3><p>Perl 6 / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/titsuki/p6-Algorithm-LibSVM" rel="noopener noreferrer">Support Vector Machines (⭐8)</a></li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/jesolem/PCV" rel="noopener noreferrer">PCV (⭐2k)</a> - Open source Python module for computer vision. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/donnyyou/PyTorchCV" rel="noopener noreferrer">PyTorchCV (⭐53)</a> - A PyTorch-Based Framework for Deep Learning in Computer Vision.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://www.nltk.org/" rel="noopener noreferrer">NLTK</a> - A leading platform for building Python programs to work with human language data.</li>
</ul>

<ul>
<li><a href="https://github.com/machinalis/yalign" rel="noopener noreferrer">YAlign (⭐130)</a> - A sentence aligner, a friendly tool for extracting parallel sentences from comparable corpora. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/tasdikrahman/spammy" rel="noopener noreferrer">spammy (⭐145)</a> - A library for email Spam filtering built on top of NLTK</li>
</ul>

<ul>
<li><a href="https://github.com/fangpenlin/loso" rel="noopener noreferrer">loso (⭐81)</a> - Another Chinese segmentation library. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/pprett/nut" rel="noopener noreferrer">nut (⭐119)</a> - Natural language Understanding Toolkit. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://pypi.org/project/bllipparser/" rel="noopener noreferrer">BLLIP Parser</a> - Python bindings for the BLLIP Natural Language Parser (also known as the Charniak-Johnson parser). <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/proycon/pynlpl" rel="noopener noreferrer">PyNLPl (⭐476)</a> - Python Natural Language Processing Library. General purpose NLP library for Python. Also contains some specific modules for parsing common NLP formats, most notably for <a href="https://proycon.github.io/folia/" rel="noopener noreferrer">FoLiA</a>, but also ARPA language models, Moses phrasetables, GIZA++ alignments.</li>
</ul>

<ul>
<li><a href="https://github.com/explosion/spaCy" rel="noopener noreferrer">spaCy (⭐33k)</a> - Industrial strength NLP with Python and Cython.</li>
</ul>

<ul>
<li><a href="https://github.com/doukremt/distance" rel="noopener noreferrer">Distance (⭐117)</a> - Levenshtein and Hamming distance computation. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://pypi.org/project/editdistance/" rel="noopener noreferrer">editdistance</a> - fast implementation of edit distance.</li>
</ul>

<ul>
<li><a href="https://github.com/dasmith/stanford-corenlp-python" rel="noopener noreferrer">stanford-corenlp-python (⭐611)</a> - Python wrapper for <a href="https://github.com/stanfordnlp/CoreNLP" rel="noopener noreferrer">Stanford CoreNLP (⭐10k)</a> <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.scipy.org/" rel="noopener noreferrer">SciPy</a> - A Python-based ecosystem of open-source software for mathematics, science, and engineering.</li>
</ul>

<ul>
<li><a href="https://www.numpy.org/" rel="noopener noreferrer">NumPy</a> - A fundamental package for scientific computing with Python.</li>
</ul>

<ul>
<li><a href="https://numba.pydata.org/" rel="noopener noreferrer">Numba</a> - Python JIT (just in time) compiler to LLVM aimed at scientific Python by the developers of Cython and NumPy.</li>
</ul>

<ul>
<li><a href="https://igraph.org/python/" rel="noopener noreferrer">igraph</a> - binding to igraph library - General purpose graph library.</li>
</ul>

<ul>
<li><a href="https://pandas.pydata.org/" rel="noopener noreferrer">Pandas</a> - A library providing high-performance, easy-to-use data structures and data analysis tools.</li>
</ul>

<ul>
<li><a href="https://github.com/mining/mining" rel="noopener noreferrer">Open Mining (⭐1.3k)</a> - Business Intelligence (BI) in Python (Pandas web interface) <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://www.pydy.org/" rel="noopener noreferrer">PyDy</a> - Short for Python Dynamics, used to assist with workflow in the modelling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.</li>
</ul>

<ul>
<li><a href="https://www.astropy.org/" rel="noopener noreferrer">astropy</a> - A community Python library for Astronomy.</li>
</ul>

<ul>
<li><a href="https://matplotlib.org/" rel="noopener noreferrer">matplotlib</a> - A Python 2D plotting library.</li>
</ul>

<ul>
<li><a href="https://github.com/altair-viz/altair" rel="noopener noreferrer">altair (⭐10k)</a> - A Python to Vega translator.</li>
</ul>

<ul>
<li><a href="https://github.com/yhat/ggpy" rel="noopener noreferrer">ggplot (⭐3.7k)</a> - Same API as ggplot2 for R. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/twitter/pycascading" rel="noopener noreferrer">pycascading (⭐221)</a> <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/cigroup-ol/windml" rel="noopener noreferrer">windML (⭐130)</a> - A Python Framework for Wind Energy Analysis and Prediction.</li>
</ul>

<ul>
<li><a href="https://github.com/numenta/nupic.cerebro2" rel="noopener noreferrer">cerebro2</a> A web-based visualization and debugging platform for NuPIC. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/htm-community/nupic.studio" rel="noopener noreferrer">NuPIC Studio (⭐95)</a> An all-in-one NuPIC Hierarchical Temporal Memory visualization and debugging super-tool! <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://seaborn.pydata.org/" rel="noopener noreferrer">Seaborn</a> - A python visualization library based on matplotlib.</li>
</ul>

<ul>
<li><a href="https://github.com/apache/incubator-superset" rel="noopener noreferrer">Superset (⭐73k)</a> - A data exploration platform designed to be visual, intuitive, and interactive.</li>
</ul>

<ul>
<li><a href="https://github.com/ayush1997/visualize_ML" rel="noopener noreferrer">visualize_ML (⭐205)</a> - A python package for data exploration and data analysis. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/jaredthecoder/BioPy" rel="noopener noreferrer">BioPy (⭐49)</a> - Biologically-Inspired and Machine Learning Algorithms in Python. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks" rel="noopener noreferrer">A gallery of interesting IPython notebooks (⭐15k)</a></li>
</ul>

<ul>
<li><a href="https://www.karsdorp.io/python-course/" rel="noopener noreferrer">Python Programming for the Humanities</a> - Course for Python programming for the Humanities, assuming no prior knowledge. Heavy focus on text processing / NLP.</li>
</ul>

<ul>
<li><a href="https://parrotprediction.teachable.com/p/practical-xgboost-in-python" rel="noopener noreferrer">Practical XGBoost in Python</a> - comprehensive online course about using XGBoost in Python.</li>
</ul>
<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/karpathy/neuraltalk2" rel="noopener noreferrer">NeuralTalk (⭐5.6k)</a> - NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/molcik/python-neuron" rel="noopener noreferrer">Neuron (⭐41)</a> - Neuron is simple class for time series predictions. It's utilize LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neural networks learned with Gradient descent or LeLevenberg–Marquardt algorithm. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Ruby / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/louismullie/treat" rel="noopener noreferrer">Treat (⭐1.4k)</a> - Text Retrieval and Annotation Toolkit, definitely the most comprehensive toolkit I’ve encountered so far for Ruby.</li>
</ul>

<ul>
<li><a href="https://github.com/aurelian/ruby-stemmer" rel="noopener noreferrer">Stemmer (⭐249)</a> - Expose libstemmer_c to Ruby. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/twitter/twitter-text/tree/master/rb" rel="noopener noreferrer">Twitter-text-rb (⭐3.1k)</a> - A library that does auto linking and extraction of usernames, lists and hashtags in tweets.</li>
</ul>
<h3><p>Ruby / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/tsycho/ruby-machine-learning" rel="noopener noreferrer">Ruby Machine Learning (⭐34)</a> - Some Machine Learning algorithms, implemented in Ruby. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/mizoR/machine-learning-ruby" rel="noopener noreferrer">Machine Learning Ruby (⭐16)</a> <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/vasinov/jruby_mahout" rel="noopener noreferrer">jRuby Mahout (⭐165)</a> - JRuby Mahout is a gem that unleashes the power of Apache Mahout in the world of JRuby. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/asafschers/scoruby" rel="noopener noreferrer">Scoruby (⭐70)</a> - Creates Random Forest classifiers from PMML files.</li>
</ul>
<h3><p>Ruby / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/chrislo/data_visualisation_ruby" rel="noopener noreferrer">data-visualization-ruby (⭐67)</a> - Source code and supporting content for my Ruby Manor presentation on Data Visualisation with Ruby. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://www.ruby-toolbox.com/projects/ruby-plot" rel="noopener noreferrer">ruby-plot</a> - gnuplot wrapper for Ruby, especially for plotting ROC curves into SVG files. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/zuhao/plotrb" rel="noopener noreferrer">plot-rb (⭐41)</a> - A plotting library in Ruby built on top of Vega and D3. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/delano/scruffy" rel="noopener noreferrer">scruffy (⭐31)</a> - A beautiful graphing toolkit for Ruby.</li>
</ul>

<ul>
<li><a href="https://github.com/glean/glean" rel="noopener noreferrer">Glean (⭐119)</a> - A data management tool for humans. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/nkallen/arel" rel="noopener noreferrer">Arel (⭐270)</a> <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Rust / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/autumnai/leaf" rel="noopener noreferrer">leaf (⭐5.5k)</a> - open source framework for machine intelligence, sharing concepts from TensorFlow and Caffe. Available under the MIT license. <a href="https://medium.com/@mjhirn/tensorflow-wins-89b78b29aafb#.s0a3uy4cc" rel="noopener noreferrer"><strong>[Deprecated]</strong></a></li>
</ul>

<ul>
<li><a href="https://github.com/jackm321/RustNN" rel="noopener noreferrer">RustNN (⭐341)</a> - RustNN is a feedforward neural network library. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>R / Data Manipulation | Data Analysis | Data Visualization</p>
</h3>
<ul>
<li><a href="https://ggplot2.tidyverse.org/" rel="noopener noreferrer">ggplot2</a> - A data visualization package based on the grammar of graphics.</li>
</ul>

<ul>
<li><a href="https://shiny.rstudio.com/" rel="noopener noreferrer">shiny</a> is the basis for truly interactive displays and dashboards in R. However, some measure of interactivity can be achieved with <a href="https://www.htmlwidgets.org/" rel="noopener noreferrer">htmlwidgets</a> bringing javascript libraries to R. These include, <a href="https://plot.ly/r/" rel="noopener noreferrer">plotly</a>, <a href="http://rstudio.github.io/dygraphs" rel="noopener noreferrer">dygraphs</a>, <a href="http://jkunst.com/highcharter/" rel="noopener noreferrer">highcharter</a>, and several others.</li>
</ul>
<h3><p>SAS / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://www.sas.com/en_us/software/visual-data-mining-machine-learning.html" rel="noopener noreferrer">Visual Data Mining and Machine Learning</a> - Interactive, automated, and programmatic modelling with the latest machine learning algorithms in and end-to-end analytics environment, from data prep to deployment. Free trial available.</li>
</ul>
<h3><p>SAS / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.sas.com/en_us/software/stat.html" rel="noopener noreferrer">SAS/STAT</a> - For conducting advanced statistical analysis.</li>
</ul>
<h3><p>SAS / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://www.sas.com/en_us/software/contextual-analysis.html" rel="noopener noreferrer">Contextual Analysis</a> - Add structure to unstructured text using a GUI.</li>
</ul>

<ul>
<li><a href="https://www.sas.com/en_us/software/sentiment-analysis.html" rel="noopener noreferrer">Sentiment Analysis</a> - Extract sentiment from text using a GUI.</li>
</ul>

<ul>
<li><a href="https://www.sas.com/en_us/software/text-miner.html" rel="noopener noreferrer">Text Miner</a> - Text mining using a GUI or code.</li>
</ul>
<h3><p>Scala / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/scalanlp/chalk" rel="noopener noreferrer">Chalk (⭐260)</a> - Chalk is a natural language processing library. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Tools / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/cloudkj/layer" rel="noopener noreferrer">layer (⭐561)</a> - Neural network inference from the command line</li>
</ul>
<h3><p>Swift / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Swift-AI/Swift-AI" rel="noopener noreferrer">Swift AI (⭐6k)</a> - Highly optimized artificial intelligence and machine learning library written in Swift.</li>
</ul>

<ul>
<li><a href="https://github.com/alejandro-isaza/BrainCore" rel="noopener noreferrer">BrainCore (⭐378)</a> - The iOS and OS X neural network framework.</li>
</ul>

<ul>
<li><a href="https://github.com/stsievert/swix" rel="noopener noreferrer">swix (⭐586)</a> - A bare bones library that includes a general matrix language and wraps some OpenCV for iOS development. <strong>[Deprecated]</strong></li>
</ul>

<ul>
<li><a href="https://github.com/KevinCoble/AIToolbox" rel="noopener noreferrer">AIToolbox (⭐802)</a> - A toolbox framework of AI modules written in Swift: Graphs/Trees, Linear Regression, Support Vector Machines, Neural Networks, PCA, KMeans, Genetic Algorithms, MDP, Mixture of Gaussians.</li>
</ul>

<ul>
<li><a href="https://github.com/SwiftBrain/awesome-CoreML-models" rel="noopener noreferrer">Awesome CoreML (⭐584)</a> - A curated list of pretrained CoreML models.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/4/"/>
    <summary>317 awesome projects updated on Jan 28 - Feb 03, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2019/2/</id>
    <title>Awesome Machine Learning Updates on Jan 14 - Jan 20, 2019</title>
    <updated>2019-01-12T07:09:46.000Z</updated>
    <published>2019-01-07T01:05:41.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/gojek/feast" rel="noopener noreferrer">Feast (⭐7k)</a> - A feature store for the management, discovery, and access of machine learning features. Feast provides a consistent view of feature data for both model training and model serving.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/yzhao062/pyod" rel="noopener noreferrer">PyOD (⭐9.8k)</a> -&gt; Python Outlier Detection, comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. Featured for Advanced models, including Neural Networks/Deep Learning and Outlier Ensembles.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2019/2/"/>
    <summary>2 awesome projects updated on Jan 14 - Jan 20, 2019</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/52/</id>
    <title>Awesome Machine Learning Updates on Dec 24 - Dec 30, 2018</title>
    <updated>2018-12-28T04:44:34.000Z</updated>
    <published>2018-12-28T04:44:34.000Z</published>
    <content type="html"><![CDATA[<h3><p>General-Purpose Machine Learning / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/RubixML" rel="noopener noreferrer">Rubix ML</a> - A high-level machine learning (ML) library that lets you build programs that learn from data using the PHP language.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/52/"/>
    <summary>1 awesome projects updated on Dec 24 - Dec 30, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/51/</id>
    <title>Awesome Machine Learning Updates on Dec 17 - Dec 23, 2018</title>
    <updated>2018-12-21T15:44:02.000Z</updated>
    <published>2018-12-21T06:56:14.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/mindsdb/mindsdb" rel="noopener noreferrer">MindsDB (⭐39k)</a> - Open Source framework to streamline use of neural networks.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/trekhleb/homemade-machine-learning" rel="noopener noreferrer">Homemade Machine Learning (⭐24k)</a> - Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/51/"/>
    <summary>2 awesome projects updated on Dec 17 - Dec 23, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/50/</id>
    <title>Awesome Machine Learning Updates on Dec 10 - Dec 16, 2018</title>
    <updated>2018-12-16T21:47:36.000Z</updated>
    <published>2018-12-11T00:01:10.000Z</published>
    <content type="html"><![CDATA[<h3><p>Clojure / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/aria42/infer" rel="noopener noreferrer">Infer (⭐176)</a> - Inference and machine learning in Clojure. <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://singa.apache.org" rel="noopener noreferrer">Apache SINGA</a> - An Apache Incubating project for developing an open source machine learning library.</li>
</ul>
<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://cran.r-project.org/web/packages/L0Learn/index.html" rel="noopener noreferrer">L0Learn</a> - L0Learn: Fast algorithms for best subset selection.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/rlan/notebooks" rel="noopener noreferrer">Notebooks (⭐34)</a> - A starter kit for Jupyter notebooks and machine learning. Companion docker images consist of all combinations of python versions, machine learning frameworks (Keras, PyTorch and Tensorflow) and CPU/CUDA versions.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/50/"/>
    <summary>4 awesome projects updated on Dec 10 - Dec 16, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/48/</id>
    <title>Awesome Machine Learning Updates on Nov 26 - Dec 02, 2018</title>
    <updated>2018-11-30T20:04:36.000Z</updated>
    <published>2018-11-30T20:04:36.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/asavinov/lambdo" rel="noopener noreferrer">Lambdo (⭐26)</a> - A workflow engine for solving machine learning problems by combining in one analysis pipeline (i) feature engineering and machine learning (ii) model training and prediction (iii) table population and column evaluation via user-defined (Python) functions.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/48/"/>
    <summary>1 awesome projects updated on Nov 26 - Dec 02, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/45/</id>
    <title>Awesome Machine Learning Updates on Nov 05 - Nov 11, 2018</title>
    <updated>2018-11-11T20:46:14.000Z</updated>
    <published>2018-11-07T18:58:52.000Z</published>
    <content type="html"><![CDATA[<h3><p>Elixir / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/mrdimosthenis/emel" rel="noopener noreferrer">emel (⭐115)</a> - A simple and functional machine learning library written in Elixir.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/scoremedia/thampi" rel="noopener noreferrer">Thampi (⭐9)</a> - Machine Learning Prediction System on AWS Lambda</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/45/"/>
    <summary>2 awesome projects updated on Nov 05 - Nov 11, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/44/</id>
    <title>Awesome Machine Learning Updates on Oct 29 - Nov 04, 2018</title>
    <updated>2018-11-01T05:13:42.000Z</updated>
    <published>2018-10-31T05:34:00.000Z</published>
    <content type="html"><![CDATA[<h3><p>Matlab / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/trekhleb/machine-learning-octave" rel="noopener noreferrer">Machine Learning in MatLab/Octave (⭐895)</a> - Examples of popular machine learning algorithms (neural networks, linear/logistic regressions, K-Means, etc.) with code examples and mathematics behind them being explained.</li>
</ul>
<h3><p>Tools / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/iterative/dvc" rel="noopener noreferrer">DVC (⭐16k)</a> - Data Science Version Control is an open-source version control system for machine learning projects with pipelines support. It makes ML projects reproducible and shareable.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/44/"/>
    <summary>2 awesome projects updated on Oct 29 - Nov 04, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/43/</id>
    <title>Awesome Machine Learning Updates on Oct 22 - Oct 28, 2018</title>
    <updated>2018-10-27T08:27:52.000Z</updated>
    <published>2018-10-26T03:12:43.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/ml5js/ml5-library" rel="noopener noreferrer">ml5 (⭐6.6k)</a> - Friendly machine learning for the web!</li>
</ul>
<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/NervanaSystems/coach" rel="noopener noreferrer">Coach</a> - Reinforcement Learning Coach by Intel® AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/43/"/>
    <summary>2 awesome projects updated on Oct 22 - Oct 28, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/42/</id>
    <title>Awesome Machine Learning Updates on Oct 15 - Oct 21, 2018</title>
    <updated>2018-10-20T00:21:37.000Z</updated>
    <published>2018-10-17T00:10:27.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/Franck-Dernoncourt/NeuroNER" rel="noopener noreferrer">NeuroNER (⭐1.7k)</a> - Named-entity recognition using neural networks providing state-of-the-art-results</li>
</ul>
<h3><p>R / Data Manipulation | Data Analysis | Data Visualization</p>
</h3>
<ul>
<li><a href="https://cran.r-project.org/web/packages/tmap/vignettes/tmap-getstarted.html" rel="noopener noreferrer">tmap</a> for visualizing geospatial data with static maps and <a href="https://rstudio.github.io/leaflet/" rel="noopener noreferrer">leaflet</a> for interactive maps</li>
</ul>

<ul>
<li><a href="https://www.rdocumentation.org/packages/tm/" rel="noopener noreferrer">tm</a> and <a href="https://quanteda.io/" rel="noopener noreferrer">quanteda</a> are the main packages for managing,  analyzing, and visualizing textual data.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/42/"/>
    <summary>3 awesome projects updated on Oct 15 - Oct 21, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/41/</id>
    <title>Awesome Machine Learning Updates on Oct 08 - Oct 14, 2018</title>
    <updated>2018-10-12T06:41:20.000Z</updated>
    <published>2018-10-08T20:31:02.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/lutzroeder/netron" rel="noopener noreferrer">Netron (⭐33k)</a> - Visualizer for machine learning models.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/dedupeio/dedupe" rel="noopener noreferrer">Dedupe (⭐4.5k)</a> - A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/41/"/>
    <summary>2 awesome projects updated on Oct 08 - Oct 14, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/40/</id>
    <title>Awesome Machine Learning Updates on Oct 01 - Oct 07, 2018</title>
    <updated>2018-10-03T18:33:09.000Z</updated>
    <published>2018-10-03T18:33:09.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/bwaldvogel/liblinear-java" rel="noopener noreferrer">liblinear-java (⭐310)</a> - Java version of liblinear.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/40/"/>
    <summary>1 awesome projects updated on Oct 01 - Oct 07, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/38/</id>
    <title>Awesome Machine Learning Updates on Sep 17 - Sep 23, 2018</title>
    <updated>2018-09-22T19:35:00.000Z</updated>
    <published>2018-09-22T19:30:20.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/plotly/dash" rel="noopener noreferrer">Dash (⭐24k)</a> - A framework for creating analytical web applications built on top of Plotly.js, React, and Flask</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/plotly/dash-svm" rel="noopener noreferrer">SVM Explorer</a> - Interactive SVM Explorer, using Dash and scikit-learn</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/38/"/>
    <summary>2 awesome projects updated on Sep 17 - Sep 23, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/37/</id>
    <title>Awesome Machine Learning Updates on Sep 10 - Sep 16, 2018</title>
    <updated>2018-09-10T14:15:01.000Z</updated>
    <published>2018-09-10T14:15:01.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/sepandhaghighi/pycm" rel="noopener noreferrer">PyCM (⭐1.5k)</a> - PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/37/"/>
    <summary>1 awesome projects updated on Sep 10 - Sep 16, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/35/</id>
    <title>Awesome Machine Learning Updates on Aug 27 - Sep 02, 2018</title>
    <updated>2018-08-30T15:56:12.000Z</updated>
    <published>2018-08-29T17:21:16.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/neptune-ml/steppy-toolkit" rel="noopener noreferrer">steppy-toolkit (⭐22)</a> -&gt; Curated collection of the neural networks, transformers and models that make your machine learning work faster and more effective.</li>
</ul>
<h3><p>Python / Kaggle Competition Source Code</p>
</h3>
<ul>
<li><a href="https://github.com/neptune-ml/open-solution-home-credit" rel="noopener noreferrer">open-solution-home-credit (⭐462)</a> -&gt; source code and <a href="https://app.neptune.ml/neptune-ml/Home-Credit-Default-Risk" rel="noopener noreferrer">experiments results</a> for <a href="https://www.kaggle.com/c/home-credit-default-risk" rel="noopener noreferrer">Home Credit Default Risk</a>.</li>
</ul>

<ul>
<li><a href="https://github.com/neptune-ml/open-solution-googleai-object-detection" rel="noopener noreferrer">open-solution-googleai-object-detection (⭐46)</a> -&gt; source code and <a href="https://app.neptune.ml/neptune-ml/Google-AI-Object-Detection-Challenge" rel="noopener noreferrer">experiments results</a> for <a href="https://www.kaggle.com/c/google-ai-open-images-object-detection-track" rel="noopener noreferrer">Google AI Open Images - Object Detection Track</a>.</li>
</ul>

<ul>
<li><a href="https://github.com/neptune-ml/open-solution-salt-identification" rel="noopener noreferrer">open-solution-salt-identification (⭐121)</a> -&gt; source code and <a href="https://app.neptune.ml/neptune-ml/Salt-Detection" rel="noopener noreferrer">experiments results</a> for <a href="https://www.kaggle.com/c/tgs-salt-identification-challenge" rel="noopener noreferrer">TGS Salt Identification Challenge</a>.</li>
</ul>

<ul>
<li><a href="https://github.com/neptune-ml/open-solution-ship-detection" rel="noopener noreferrer">open-solution-ship-detection (⭐65)</a> -&gt; source code and <a href="https://app.neptune.ml/neptune-ml/Ships" rel="noopener noreferrer">experiments results</a> for <a href="https://www.kaggle.com/c/airbus-ship-detection" rel="noopener noreferrer">Airbus Ship Detection Challenge</a>.</li>
</ul>

<ul>
<li><a href="https://github.com/neptune-ml/open-solution-data-science-bowl-2018" rel="noopener noreferrer">open-solution-data-science-bowl-2018 (⭐155)</a> -&gt; source code and <a href="https://app.neptune.ml/neptune-ml/Data-Science-Bowl-2018" rel="noopener noreferrer">experiments results</a> for <a href="https://www.kaggle.com/c/data-science-bowl-2018" rel="noopener noreferrer">2018 Data Science Bowl</a>.</li>
</ul>

<ul>
<li><a href="https://github.com/neptune-ml/open-solution-value-prediction" rel="noopener noreferrer">open-solution-value-prediction (⭐39)</a> -&gt; source code and <a href="https://app.neptune.ml/neptune-ml/Santander-Value-Prediction-Challenge" rel="noopener noreferrer">experiments results</a> for <a href="https://www.kaggle.com/c/santander-value-prediction-challenge" rel="noopener noreferrer">Santander Value Prediction Challenge</a>.</li>
</ul>

<ul>
<li><a href="https://github.com/neptune-ml/open-solution-toxic-comments" rel="noopener noreferrer">open-solution-toxic-comments (⭐155)</a> -&gt; source code for <a href="https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge" rel="noopener noreferrer">Toxic Comment Classification Challenge</a>.</li>
</ul>
<h3><p>Swift / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/denissimon/prediction-builder-swift" rel="noopener noreferrer">PredictionBuilder (⭐12)</a> - A library for machine learning that builds predictions using a linear regression.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/35/"/>
    <summary>9 awesome projects updated on Aug 27 - Sep 02, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/34/</id>
    <title>Awesome Machine Learning Updates on Aug 20 - Aug 26, 2018</title>
    <updated>2018-08-25T14:51:36.000Z</updated>
    <published>2018-08-25T14:51:36.000Z</published>
    <content type="html"><![CDATA[<h3><p>.NET / Computer Vision</p>
</h3>
<ul>
<li><a href="http://www.emgu.com/wiki/index.php/Main_Page" rel="noopener noreferrer">Emgu CV</a> - Cross platform wrapper of OpenCV which can be compiled in Mono to be run on Windows, Linus, Mac OS X, iOS, and Android.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/34/"/>
    <summary>1 awesome projects updated on Aug 20 - Aug 26, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/33/</id>
    <title>Awesome Machine Learning Updates on Aug 13 - Aug 19, 2018</title>
    <updated>2018-08-17T16:50:18.000Z</updated>
    <published>2018-08-15T14:56:09.000Z</published>
    <content type="html"><![CDATA[<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/MaxHalford/eaopt" rel="noopener noreferrer">eaopt (⭐907)</a> - An evolutionary optimization library.</li>
</ul>
<h3><p>General-Purpose Machine Learning / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/fulldecent/19-questions" rel="noopener noreferrer">19 Questions (⭐16)</a> - A machine learning / bayesian inference assigning attributes to objects.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/snipsco/snips-nlu" rel="noopener noreferrer">Snips NLU (⭐4k)</a> - Natural Language Understanding library for intent classification and entity extraction</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/keras-team/keras" rel="noopener noreferrer">keras (⭐64k)</a> - High-level neural networks frontend for <a href="https://github.com/tensorflow/tensorflow" rel="noopener noreferrer">TensorFlow (⭐195k)</a>, <a href="https://github.com/Microsoft/CNTK" rel="noopener noreferrer">CNTK (⭐18k)</a> and <a href="https://github.com/Theano/Theano" rel="noopener noreferrer">Theano (⭐10k)</a>.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/33/"/>
    <summary>4 awesome projects updated on Aug 13 - Aug 19, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/31/</id>
    <title>Awesome Machine Learning Updates on Jul 30 - Aug 05, 2018</title>
    <updated>2018-08-02T18:10:18.000Z</updated>
    <published>2018-08-02T18:10:18.000Z</published>
    <content type="html"><![CDATA[<h3><p>TensorFlow / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://golden.com/wiki/TensorFlow" rel="noopener noreferrer">Golden TensorFlow</a> - A page of content on TensorFlow, including academic papers and links to related topics.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/31/"/>
    <summary>1 awesome projects updated on Jul 30 - Aug 05, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/28/</id>
    <title>Awesome Machine Learning Updates on Jul 09 - Jul 15, 2018</title>
    <updated>2018-07-12T14:05:07.000Z</updated>
    <published>2018-07-12T14:05:07.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/albu/albumentations" rel="noopener noreferrer">albumentations (⭐15k)</a> - А fast and framework agnostic image augmentation library that implements a diverse set of augmentation techniques. Supports classification, segmentation, detection out of the box. Was used to win a number of Deep Learning competitions at Kaggle, Topcoder and those that were a part of the CVPR workshops.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/28/"/>
    <summary>1 awesome projects updated on Jul 09 - Jul 15, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/27/</id>
    <title>Awesome Machine Learning Updates on Jul 02 - Jul 08, 2018</title>
    <updated>2018-07-06T03:02:30.000Z</updated>
    <published>2018-07-06T03:02:30.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/openai/roboschool" rel="noopener noreferrer">Roboschool (⭐2.2k)</a> - Open-source software for robot simulation, integrated with OpenAI Gym.</li>
</ul>

<ul>
<li><a href="https://github.com/openai/retro" rel="noopener noreferrer">Retro (⭐3.6k)</a> - Retro Games in Gym</li>
</ul>

<ul>
<li><a href="https://github.com/kengz/SLM-Lab" rel="noopener noreferrer">SLM Lab (⭐1.3k)</a> - Modular Deep Reinforcement Learning framework in PyTorch.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/27/"/>
    <summary>3 awesome projects updated on Jul 02 - Jul 08, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/26/</id>
    <title>Awesome Machine Learning Updates on Jun 25 - Jul 01, 2018</title>
    <updated>2018-06-28T09:48:03.000Z</updated>
    <published>2018-06-25T09:05:22.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://mathema.tician.de/software/pycuda/" rel="noopener noreferrer">PyCUDA</a> - Python interface to CUDA</li>
</ul>
<h3><p>JavaScript / Demos and Scripts</p>
</h3>
<ul>
<li><a href="https://github.com/sta-ger/TheBot" rel="noopener noreferrer">The Bot (⭐6)</a> - Example of how the neural network learns to predict the angle between two points created with <a href="https://github.com/cazala/synaptic" rel="noopener noreferrer">Synaptic (⭐6.9k)</a>.</li>
</ul>

<ul>
<li><a href="https://github.com/sta-ger/HalfBeer" rel="noopener noreferrer">Half Beer (⭐6)</a> - Beer glass classifier created with <a href="https://github.com/cazala/synaptic" rel="noopener noreferrer">Synaptic (⭐6.9k)</a>.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/flennerhag/mlens" rel="noopener noreferrer">mlens (⭐864)</a> - A high performance, memory efficient, maximally parallelized ensemble learning, integrated with scikit-learn.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/26/"/>
    <summary>4 awesome projects updated on Jun 25 - Jul 01, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/22/</id>
    <title>Awesome Machine Learning Updates on May 28 - Jun 03, 2018</title>
    <updated>2018-05-28T17:35:00.000Z</updated>
    <published>2018-05-28T17:35:00.000Z</published>
    <content type="html"><![CDATA[<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/picnicml/doddle-model" rel="noopener noreferrer">doddle-model (⭐139)</a> - An in-memory machine learning library built on top of Breeze. It provides immutable objects and exposes its functionality through a scikit-learn-like API.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/22/"/>
    <summary>1 awesome projects updated on May 28 - Jun 03, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/19/</id>
    <title>Awesome Machine Learning Updates on May 07 - May 13, 2018</title>
    <updated>2018-05-11T23:52:21.000Z</updated>
    <published>2018-05-08T02:41:22.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://js.tensorflow.org/" rel="noopener noreferrer">TensorFlow.js</a> - A WebGL accelerated, browser based JavaScript library for training and deploying ML models.</li>
</ul>
<h3><p>.NET / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/giacomelli/GeneticSharp" rel="noopener noreferrer">GeneticSharp (⭐1.4k)</a> - Multi-platform genetic algorithm library for .NET Core and .NET Framework. The library has several implementations of GA operators, like: selection, crossover, mutation, reinsertion and termination.</li>
</ul>

<ul>
<li><a href="https://github.com/dotnet/machinelearning" rel="noopener noreferrer">ML.NET (⭐9.3k)</a> - ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers. ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, PowerPoint, Excel and more.</li>
</ul>

<ul>
<li><a href="https://github.com/fsprojects/Vulpes" rel="noopener noreferrer">Vulpes (⭐116)</a> - Deep belief and deep learning implementation written in F# and leverages CUDA GPU execution with Alea.cuBase.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/19/"/>
    <summary>4 awesome projects updated on May 07 - May 13, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/18/</id>
    <title>Awesome Machine Learning Updates on Apr 30 - May 06, 2018</title>
    <updated>2018-05-04T14:53:55.000Z</updated>
    <published>2018-05-01T14:16:44.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/aksnzhy/xlearn" rel="noopener noreferrer">xLearn (⭐3.1k)</a> - A high performance, easy-to-use, and scalable machine learning package, which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data, which is very common in Internet services such as online advertisement and recommender systems.</li>
</ul>
<h3><p>Rust / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/avinashshenoy97/RusticSOM" rel="noopener noreferrer">RusticSOM (⭐37)</a> - A Rust library for Self Organising Maps (SOM).</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/18/"/>
    <summary>2 awesome projects updated on Apr 30 - May 06, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/12/</id>
    <title>Awesome Machine Learning Updates on Mar 19 - Mar 25, 2018</title>
    <updated>2018-03-23T17:35:53.000Z</updated>
    <published>2018-03-23T17:35:53.000Z</published>
    <content type="html"><![CDATA[<h3><p>Matlab / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/apache/incubator-mxnet/" rel="noopener noreferrer">MXNet (⭐21k)</a> - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, JavaScript and more.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/12/"/>
    <summary>1 awesome projects updated on Mar 19 - Mar 25, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/10/</id>
    <title>Awesome Machine Learning Updates on Mar 05 - Mar 11, 2018</title>
    <updated>2018-03-06T10:11:32.000Z</updated>
    <published>2018-03-06T10:11:32.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/nuanio/xgboost-node" rel="noopener noreferrer">xgboost-node (⭐48)</a> - Run XGBoost model and make predictions in Node.js.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/10/"/>
    <summary>1 awesome projects updated on Mar 05 - Mar 11, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/9/</id>
    <title>Awesome Machine Learning Updates on Feb 26 - Mar 04, 2018</title>
    <updated>2018-02-27T12:41:17.000Z</updated>
    <published>2018-02-27T12:41:17.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/siavashserver/neonrvm" rel="noopener noreferrer">neonrvm (⭐40)</a> - neonrvm is an open source machine learning library based on RVM technique. It's written in C programming language and comes with Python programming language bindings.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/9/"/>
    <summary>1 awesome projects updated on Feb 26 - Mar 04, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/7/</id>
    <title>Awesome Machine Learning Updates on Feb 12 - Feb 18, 2018</title>
    <updated>2018-02-12T09:59:34.000Z</updated>
    <published>2018-02-12T09:53:49.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/jgreenemi/MLPleaseHelp" rel="noopener noreferrer">MLPleaseHelp</a> - MLPleaseHelp is a simple ML resource search engine. You can use this search engine right now at <a href="https://jgreenemi.github.io/MLPleaseHelp/" rel="noopener noreferrer">https://jgreenemi.github.io/MLPleaseHelp/</a>, provided via GitHub Pages.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/jgreenemi/Parris" rel="noopener noreferrer">Parris (⭐314)</a> - Parris, the automated infrastructure setup tool for machine learning algorithms.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/7/"/>
    <summary>2 awesome projects updated on Feb 12 - Feb 18, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/6/</id>
    <title>Awesome Machine Learning Updates on Feb 05 - Feb 11, 2018</title>
    <updated>2018-02-09T07:57:46.000Z</updated>
    <published>2018-02-07T06:45:36.000Z</published>
    <content type="html"><![CDATA[<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/catboost/catboost" rel="noopener noreferrer">CatBoost (⭐8.9k)</a> - General purpose gradient boosting on decision trees library with categorical features support out of the box for R.</li>
</ul>
<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/transcranial/keras-js" rel="noopener noreferrer">Keras.js (⭐5k)</a> - Run Keras models in the browser, with GPU support provided by WebGL 2.</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/marcotcr/lime" rel="noopener noreferrer">lime (⭐12k)</a> - Lime is about explaining what machine learning classifiers (or models) are doing. It is able to explain any black box classifier, with two or more classes.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/amueller/introduction_to_ml_with_python" rel="noopener noreferrer">Introduction to Machine Learning with Python (⭐8.1k)</a> - Notebooks and code for the book "Introduction to Machine Learning with Python"</li>
</ul>

<ul>
<li><a href="https://github.com/wesm/pydata-book" rel="noopener noreferrer">Pydata book (⭐25k)</a> - Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/6/"/>
    <summary>5 awesome projects updated on Feb 05 - Feb 11, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2018/1/</id>
    <title>Awesome Machine Learning Updates on Jan 01 - Jan 07, 2018</title>
    <updated>2018-01-01T21:01:19.000Z</updated>
    <published>2018-01-01T21:01:19.000Z</published>
    <content type="html"><![CDATA[<h3><p>Lua / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://torch.ch/" rel="noopener noreferrer">Torch7</a><ul>
<li><a href="https://github.com/deepmind/torch-cephes" rel="noopener noreferrer">cephes (⭐50)</a> - Cephes mathematical functions library, wrapped for Torch. Provides and wraps the 180+ special mathematical functions from the Cephes mathematical library, developed by Stephen L. Moshier. It is used, among many other places, at the heart of SciPy. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/twitter/torch-autograd" rel="noopener noreferrer">autograd (⭐559)</a> - Autograd automatically differentiates native Torch code. Inspired by the original Python version.</li>
<li><a href="https://github.com/torch/graph" rel="noopener noreferrer">graph (⭐38)</a> - Graph package for Torch. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/deepmind/torch-randomkit" rel="noopener noreferrer">randomkit (⭐34)</a> - Numpy's randomkit, wrapped for Torch. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/soumith/torch-signal" rel="noopener noreferrer">signal (⭐49)</a> - A signal processing toolbox for Torch-7. FFT, DCT, Hilbert, cepstrums, stft.</li>
<li><a href="https://github.com/torch/nn" rel="noopener noreferrer">nn (⭐1.4k)</a> - Neural Network package for Torch.</li>
<li><a href="https://github.com/torchnet/torchnet" rel="noopener noreferrer">torchnet (⭐988)</a> - framework for torch which provides a set of abstractions aiming at encouraging code re-use as well as encouraging modular programming.</li>
<li><a href="https://github.com/torch/nngraph" rel="noopener noreferrer">nngraph (⭐299)</a> - This package provides graphical computation for nn library in Torch7.</li>
<li><a href="https://github.com/clementfarabet/lua---nnx" rel="noopener noreferrer">nnx (⭐96)</a> - A completely unstable and experimental package that extends Torch's builtin nn library.</li>
<li><a href="https://github.com/Element-Research/rnn" rel="noopener noreferrer">rnn (⭐942)</a> - A Recurrent Neural Network library that extends Torch's nn. RNNs, LSTMs, GRUs, BRNNs, BLSTMs, etc.</li>
<li><a href="https://github.com/Element-Research/dpnn" rel="noopener noreferrer">dpnn (⭐191)</a> - Many useful features that aren't part of the main nn package.</li>
<li><a href="https://github.com/nicholas-leonard/dp" rel="noopener noreferrer">dp (⭐339)</a> - A deep learning library designed for streamlining research and development using the Torch7 distribution. It emphasizes flexibility through the elegant use of object-oriented design patterns. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/torch/optim" rel="noopener noreferrer">optim (⭐197)</a> - An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.</li>
<li><a href="https://github.com/koraykv/unsup" rel="noopener noreferrer">unsup (⭐86)</a> - A package for unsupervised learning in Torch. Provides modules that are compatible with nn (LinearPsd, ConvPsd, AutoEncoder, ...), and self-contained algorithms (k-means, PCA). <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/clementfarabet/manifold" rel="noopener noreferrer">manifold (⭐142)</a> - A package to manipulate manifolds.</li>
<li><a href="https://github.com/koraykv/torch-svm" rel="noopener noreferrer">svm (⭐44)</a> - Torch-SVM library. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/clementfarabet/lbfgs" rel="noopener noreferrer">lbfgs (⭐2)</a> - FFI Wrapper for liblbfgs. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/clementfarabet/vowpal_wabbit" rel="noopener noreferrer">vowpalwabbit (⭐2)</a> - An old vowpalwabbit interface to torch. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/clementfarabet/lua---opengm" rel="noopener noreferrer">OpenGM (⭐8)</a> - OpenGM is a C++ library for graphical modelling, and inference. The Lua bindings provide a simple way of describing graphs, from Lua, and then optimizing them with OpenGM. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/MichaelMathieu/lua---spaghetti" rel="noopener noreferrer">spaghetti (⭐2)</a> - Spaghetti (sparse linear) module for torch7 by @MichaelMathieu <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/ocallaco/LuaSHkit" rel="noopener noreferrer">LuaSHKit (⭐3)</a> - A Lua wrapper around the Locality sensitive hashing library SHKit <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/rlowrance/kernel-smoothers" rel="noopener noreferrer">kernel smoothing (⭐5)</a> - KNN, kernel-weighted average, local linear regression smoothers. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/torch/cutorch" rel="noopener noreferrer">cutorch (⭐338)</a> - Torch CUDA Implementation.</li>
<li><a href="https://github.com/torch/cunn" rel="noopener noreferrer">cunn (⭐214)</a> - Torch CUDA Neural Network Implementation.</li>
<li><a href="https://github.com/clementfarabet/lua---imgraph" rel="noopener noreferrer">imgraph (⭐22)</a> - An image/graph library for Torch. This package provides routines to construct graphs on images, segment them, build trees out of them, and convert them back to images. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/clementfarabet/videograph" rel="noopener noreferrer">videograph (⭐9)</a> - A video/graph library for Torch. This package provides routines to construct graphs on videos, segment them, build trees out of them, and convert them back to videos. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/marcoscoffier/torch-saliency" rel="noopener noreferrer">saliency (⭐7)</a> - code and tools around integral images. A library for finding interest points based on fast integral histograms. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/marcoscoffier/lua---stitch" rel="noopener noreferrer">stitch (⭐4)</a> - allows us to use hugin to stitch images and apply same stitching to a video sequence. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/marcoscoffier/lua---sfm" rel="noopener noreferrer">sfm (⭐3)</a> - A bundle adjustment/structure from motion package. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/koraykv/fex" rel="noopener noreferrer">fex (⭐10)</a> - A package for feature extraction in Torch. Provides SIFT and dSIFT modules. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/sermanet/OverFeat" rel="noopener noreferrer">OverFeat (⭐601)</a> - A state-of-the-art generic dense feature extractor. <strong>[Deprecated]</strong></li>
<li><a href="https://github.com/facebookresearch/wav2letter" rel="noopener noreferrer">wav2letter (⭐6.4k)</a> - a simple and efficient end-to-end Automatic Speech Recognition (ASR) system from Facebook AI Research.</li>
</ul>
</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2018/1/"/>
    <summary>1 awesome projects updated on Jan 01 - Jan 07, 2018</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/51/</id>
    <title>Awesome Machine Learning Updates on Dec 18 - Dec 24, 2017</title>
    <updated>2017-12-19T03:09:47.000Z</updated>
    <published>2017-12-18T08:38:11.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/cnclabs/proNet-core" rel="noopener noreferrer">proNet-core (⭐3)</a> - A general-purpose network embedding framework: pair-wise representations optimization Network Edit.</li>
</ul>
<h3><p>Go / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/neurosnap/sentences" rel="noopener noreferrer">sentences (⭐467)</a> - Golang implementation of Punkt sentence tokenizer.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/51/"/>
    <summary>2 awesome projects updated on Dec 18 - Dec 24, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/45/</id>
    <title>Awesome Machine Learning Updates on Nov 06 - Nov 12, 2017</title>
    <updated>2017-11-07T04:23:20.000Z</updated>
    <published>2017-11-07T04:23:20.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/omimo/xRBM" rel="noopener noreferrer">xRBM (⭐55)</a> - A library for Restricted Boltzmann Machine (RBM) and its conditional variants in Tensorflow.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/45/"/>
    <summary>1 awesome projects updated on Nov 06 - Nov 12, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/44/</id>
    <title>Awesome Machine Learning Updates on Oct 30 - Nov 05, 2017</title>
    <updated>2017-11-01T21:34:09.000Z</updated>
    <published>2017-11-01T01:40:56.000Z</published>
    <content type="html"><![CDATA[<h3><p>C / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/liuliu/ccv" rel="noopener noreferrer">CCV (⭐7.2k)</a> - C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library.</li>
</ul>
<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://dlib.net/ml.html" rel="noopener noreferrer">DLib</a> - A suite of ML tools designed to be easy to imbed in other applications.</li>
</ul>

<ul>
<li><a href="http://mc-stan.org/" rel="noopener noreferrer">Stan</a> - A probabilistic programming language implementing full Bayesian statistical inference with Hamiltonian Monte Carlo sampling.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/shogun-toolbox/shogun" rel="noopener noreferrer">Shogun (⭐3.1k)</a> - The Shogun Machine Learning Toolbox.</li>
</ul>

<ul>
<li><a href="https://github.com/dmlc/xgboost" rel="noopener noreferrer">XGBoost (⭐28k)</a> - Python bindings for eXtreme Gradient Boosting (Tree) Library.</li>
</ul>

<ul>
<li><a href="https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers" rel="noopener noreferrer">Bayesian Methods for Hackers (⭐28k)</a> - Book/iPython notebooks on Probabilistic Programming in Python.</li>
</ul>

<ul>
<li><a href="https://github.com/machinalis/featureforge" rel="noopener noreferrer">Featureforge (⭐386)</a> A set of tools for creating and testing machine learning features, with a scikit-learn compatible API.</li>
</ul>

<ul>
<li><a href="https://github.com/AllenDowney/ThinkBayes" rel="noopener noreferrer">thinking bayes (⭐1.7k)</a> - Book on Bayesian Analysis.</li>
</ul>

<ul>
<li><a href="https://github.com/nilearn/nilearn" rel="noopener noreferrer">nilearn (⭐1.4k)</a> - Machine learning for NeuroImaging in Python.</li>
</ul>

<ul>
<li><a href="https://github.com/Theano/Theano/" rel="noopener noreferrer">Theano (⭐10k)</a> - Optimizing GPU-meta-programming code generating array oriented optimizing math compiler in Python.</li>
</ul>

<ul>
<li><a href="https://github.com/tensorflow/tensorflow/" rel="noopener noreferrer">TensorFlow (⭐195k)</a> - Open source software library for numerical computation using data flow graphs.</li>
</ul>

<ul>
<li><a href="https://github.com/mnielsen/neural-networks-and-deep-learning" rel="noopener noreferrer">Neural Networks and Deep Learning (⭐18k)</a> - Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].</li>
</ul>

<ul>
<li><a href="https://github.com/spotify/annoy" rel="noopener noreferrer">Annoy (⭐14k)</a> - Approximate nearest neighbours implementation.</li>
</ul>

<ul>
<li><a href="https://github.com/AmazaspShumik/sklearn-bayes" rel="noopener noreferrer">skbayes (⭐523)</a> - Python package for Bayesian Machine Learning with scikit-learn API.</li>
</ul>

<ul>
<li><a href="https://github.com/reiinakano/xcessiv" rel="noopener noreferrer">Xcessiv (⭐1.3k)</a> - A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling.</li>
</ul>
<h3><p>C++ / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/BLLIP/bllip-parser" rel="noopener noreferrer">BLLIP Parser (⭐228)</a> - BLLIP Natural Language Parser (also known as the Charniak-Johnson parser).</li>
</ul>
<h3><p>Common Lisp / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/masatoi/cl-online-learning" rel="noopener noreferrer">cl-online-learning (⭐49)</a> - Online learning algorithms (Perceptron, AROW, SCW, Logistic Regression).</li>
</ul>

<ul>
<li><a href="https://github.com/masatoi/cl-random-forest" rel="noopener noreferrer">cl-random-forest (⭐60)</a> - Implementation of Random Forest in Common Lisp.</li>
</ul>
<h3><p>Clojure / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/dakrone/clojure-opennlp" rel="noopener noreferrer">Clojure-openNLP (⭐757)</a> - Natural Language Processing in Clojure (opennlp).</li>
</ul>

<ul>
<li><a href="https://github.com/r0man/inflections-clj" rel="noopener noreferrer">Infections-clj (⭐221)</a> - Rails-like inflection library for Clojure and ClojureScript.</li>
</ul>
<h3><p>Clojure / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/clojurewerkz/envision" rel="noopener noreferrer">Envision (⭐76)</a> - Clojure Data Visualisation library, based on Statistiker and D3.</li>
</ul>
<h3><p>Go / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/goml/gobrain" rel="noopener noreferrer">gobrain (⭐564)</a> - Neural Networks written in Go.</li>
</ul>
<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/datumbox/datumbox-framework" rel="noopener noreferrer">Datumbox (⭐1.1k)</a> - Machine Learning framework for rapid development of Machine Learning and Statistical applications.</li>
</ul>

<ul>
<li><a href="https://github.com/numenta/htm.java" rel="noopener noreferrer">htm.java (⭐318)</a> - General Machine Learning library using Numenta’s Cortical Learning Algorithm.</li>
</ul>

<ul>
<li><a href="https://github.com/apache/mahout" rel="noopener noreferrer">Mahout (⭐2.3k)</a> - Distributed machine learning.</li>
</ul>

<ul>
<li><a href="https://github.com/padreati/rapaio" rel="noopener noreferrer">rapaio (⭐78)</a> - statistics, data mining and machine learning toolbox in Java.</li>
</ul>

<ul>
<li><a href="https://rapidminer.com" rel="noopener noreferrer">RapidMiner</a> - RapidMiner integration into Java code.</li>
</ul>
<h3><p>Java / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/cloudera/impala" rel="noopener noreferrer">Impala (⭐34)</a> - Real-time Query for Hadoop.</li>
</ul>
<h3><p>Java / Deep Learning</p>
</h3>
<ul>
<li><a href="https://github.com/deeplearning4j/deeplearning4j" rel="noopener noreferrer">Deeplearning4j (⭐14k)</a> - Scalable deep learning for industry with parallel GPUs.</li>
</ul>
<h3><p>JavaScript / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/twitter/twitter-text" rel="noopener noreferrer">Twitter-text (⭐3.1k)</a> - A JavaScript implementation of Twitter's text processing library.</li>
</ul>

<ul>
<li><a href="https://github.com/NaturalNode/natural" rel="noopener noreferrer">natural (⭐11k)</a> - General natural language facilities for node.</li>
</ul>

<ul>
<li><a href="https://github.com/loadfive/Knwl.js" rel="noopener noreferrer">Knwl.js (⭐5.3k)</a> - A Natural Language Processor in JS.</li>
</ul>
<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://code.google.com/archive/p/figue" rel="noopener noreferrer">figue</a> - K-means, fuzzy c-means and agglomerative clustering.</li>
</ul>

<ul>
<li><a href="https://github.com/lukapopijac/gaussian-mixture-model" rel="noopener noreferrer">Gaussian Mixture Model (⭐30)</a> - Unsupervised machine learning with multivariate Gaussian mixture model.</li>
</ul>

<ul>
<li><a href="https://github.com/mil-tokyo" rel="noopener noreferrer">mil-tokyo</a> - List of several machine learning libraries.</li>
</ul>

<ul>
<li><a href="https://github.com/cazala/synaptic" rel="noopener noreferrer">Synaptic (⭐6.9k)</a> - Architecture-free neural network library for Node.js and the browser.</li>
</ul>

<ul>
<li><a href="https://github.com/NathanEpstein/kNear" rel="noopener noreferrer">kNear (⭐48)</a> - JavaScript implementation of the k nearest neighbors algorithm for supervised learning.</li>
</ul>

<ul>
<li><a href="https://github.com/NathanEpstein/Pavlov.js" rel="noopener noreferrer">Pavlov.js (⭐498)</a> - Reinforcement learning using Markov Decision Processes.</li>
</ul>
<h3><p>Julia / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/JuliaStats/MLBase.jl" rel="noopener noreferrer">MLBase (⭐186)</a> - A set of functions to support the development of machine learning algorithms.</li>
</ul>

<ul>
<li><a href="https://github.com/trthatcher/DiscriminantAnalysis.jl" rel="noopener noreferrer">DA (⭐10)</a> - Julia package for Regularized Discriminant Analysis.</li>
</ul>

<ul>
<li><a href="https://github.com/dmbates/MixedModels.jl" rel="noopener noreferrer">Mixed Models (⭐443)</a> - A Julia package for fitting (statistical) mixed-effects models.</li>
</ul>

<ul>
<li><a href="https://github.com/bensadeghi/DecisionTree.jl" rel="noopener noreferrer">Decision Tree (⭐9)</a> - Decision Tree Classifier and Regressor.</li>
</ul>

<ul>
<li><a href="https://github.com/compressed/BackpropNeuralNet.jl" rel="noopener noreferrer">Neural (⭐48)</a> - A neural network in Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/brian-j-smith/Mamba.jl" rel="noopener noreferrer">Mamba (⭐259)</a> - Markov chain Monte Carlo (MCMC) for Bayesian analysis in Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/GLM.jl" rel="noopener noreferrer">GLM (⭐636)</a> - Generalized linear models in Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/STOR-i/GaussianProcesses.jl" rel="noopener noreferrer">Gaussian Processes (⭐319)</a> - Julia package for Gaussian processes.</li>
</ul>

<ul>
<li><a href="https://github.com/simonster/GLMNet.jl" rel="noopener noreferrer">GLMNet (⭐104)</a> - Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/KernelDensity.jl" rel="noopener noreferrer">Kernel Density (⭐201)</a> - Kernel density estimators for Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/NMF.jl" rel="noopener noreferrer">NMF (⭐93)</a> - A Julia package for non-negative matrix factorization.</li>
</ul>

<ul>
<li><a href="https://github.com/dmlc/XGBoost.jl" rel="noopener noreferrer">XGBoost (⭐305)</a> - eXtreme Gradient Boosting Package in Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/wildart/ManifoldLearning.jl" rel="noopener noreferrer">ManifoldLearning (⭐95)</a> - A Julia package for manifold learning and nonlinear dimensionality reduction.</li>
</ul>

<ul>
<li><a href="https://github.com/hshindo/Merlin.jl" rel="noopener noreferrer">Merlin (⭐146)</a> - Flexible Deep Learning Framework in Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/davidavdav/ROCAnalysis.jl" rel="noopener noreferrer">ROCAnalysis (⭐33)</a> - Receiver Operating Characteristics and functions for evaluation probabilistic binary classifiers.</li>
</ul>

<ul>
<li><a href="https://github.com/davidavdav/GaussianMixtures.jl" rel="noopener noreferrer">GaussianMixtures (⭐107)</a> - Large scale Gaussian Mixture Models.</li>
</ul>

<ul>
<li><a href="https://github.com/cstjean/ScikitLearn.jl" rel="noopener noreferrer">ScikitLearn (⭐559)</a> - Julia implementation of the scikit-learn API.</li>
</ul>

<ul>
<li><a href="https://github.com/denizyuret/Knet.jl" rel="noopener noreferrer">Knet (⭐1.4k)</a> - Koç University Deep Learning Framework.</li>
</ul>
<h3><p>Julia / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/IainNZ/GraphLayout.jl" rel="noopener noreferrer">Graph Layout (⭐45)</a> - Graph layout algorithms in pure Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaGraphs/LightGraphs.jl" rel="noopener noreferrer">LightGraphs (⭐666)</a> - Graph modelling and analysis.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/HypothesisTests.jl" rel="noopener noreferrer">Hypothesis Tests (⭐317)</a> - Hypothesis tests for Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/johnmyleswhite/RDatasets.jl" rel="noopener noreferrer">RDataSets (⭐166)</a> - Julia package for loading many of the data sets available in R.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/TimeSeries.jl" rel="noopener noreferrer">Time Series (⭐368)</a> - Time series toolkit for Julia.</li>
</ul>

<ul>
<li><a href="https://github.com/lindahua/Sampling.jl" rel="noopener noreferrer">Sampling (⭐1)</a> - Basic sampling algorithms for Julia.</li>
</ul>
<h3><p>Julia / Misc Stuff / Presentations</p>
</h3>
<ul>
<li><a href="https://github.com/JuliaCon/presentations" rel="noopener noreferrer">JuliaCon Presentations (⭐70)</a> - Presentations for JuliaCon.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaImages/Images.jl" rel="noopener noreferrer">Images (⭐551)</a> - An image library for Julia.</li>
</ul>
<h3><p>Lua / Demos and Scripts</p>
</h3>
<ul>
<li><a href="https://github.com/fidlej/aledataset" rel="noopener noreferrer">Atari2600 (⭐19)</a> - Scripts to generate a dataset with static frames from the Arcade Learning Environment.</li>
</ul>
<h3><p>Matlab / Computer Vision</p>
</h3>
<ul>
<li><a href="http://www.cmap.polytechnique.fr/~peyre/download/" rel="noopener noreferrer">Bandlets</a> - MATLAB code for bandlet transform.</li>
</ul>
<h3><p>Matlab / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://www.cs.toronto.edu/~hinton/MatlabForSciencePaper.html" rel="noopener noreferrer">Training a deep autoencoder or a classifier
on MNIST digits</a> - Training a deep autoencoder or a classifier
on MNIST digits[DEEP LEARNING].</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/machinalis/quepy" rel="noopener noreferrer">Quepy (⭐1.3k)</a> - A python framework to transform natural language questions to queries in a database query language.</li>
</ul>

<ul>
<li><a href="https://github.com/proycon/python-ucto" rel="noopener noreferrer">python-ucto (⭐31)</a> - Python binding to ucto (a unicode-aware rule-based tokenizer for various languages).</li>
</ul>

<ul>
<li><a href="https://github.com/seatgeek/fuzzywuzzy" rel="noopener noreferrer">Fuzzy Wuzzy (⭐9.3k)</a> - Fuzzy String Matching in Python.</li>
</ul>

<ul>
<li><a href="https://github.com/chartbeat-labs/textacy" rel="noopener noreferrer">textacy (⭐2.2k)</a> - higher-level NLP built on Spacy.</li>
</ul>

<ul>
<li><a href="https://github.com/cltk/cltk" rel="noopener noreferrer">CLTK (⭐903)</a> - The Classical Language Toolkit.</li>
</ul>

<ul>
<li><a href="https://github.com/PPACI/yase" rel="noopener noreferrer">yase (⭐14)</a> - Transcode sentence (or other sequence) to list of word vector.</li>
</ul>

<ul>
<li><a href="https://github.com/aboSamoor/polyglot" rel="noopener noreferrer">Polyglot (⭐2.4k)</a> - Multilingual text (NLP) processing toolkit.</li>
</ul>

<ul>
<li><a href="https://github.com/facebookresearch/DrQA" rel="noopener noreferrer">DrQA (⭐4.5k)</a> - Reading Wikipedia to answer open-domain questions.</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/vispy/vispy" rel="noopener noreferrer">vispy (⭐3.6k)</a> - GPU-based high-performance interactive OpenGL 2D/3D data visualization library.</li>
</ul>

<ul>
<li><a href="https://github.com/sparklingpandas/sparklingpandas" rel="noopener noreferrer">SparklingPandas (⭐362)</a> Pandas on PySpark (POPS).</li>
</ul>

<ul>
<li><a href="https://github.com/bloomberg/bqplot" rel="noopener noreferrer">bqplot (⭐3.7k)</a> - An API for plotting in Jupyter (IPython).</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/Wavelets/diffusion-segmentation" rel="noopener noreferrer">Diffusion Segmentation (⭐2)</a> - A collection of image segmentation algorithms based on diffusion methods.</li>
</ul>

<ul>
<li><a href="https://github.com/Wavelets/scipy-tutorials" rel="noopener noreferrer">Scipy Tutorials (⭐2)</a> - SciPy tutorials. This is outdated, check out scipy-lecture-notes.</li>
</ul>

<ul>
<li><a href="https://github.com/marcelcaraciolo/crab" rel="noopener noreferrer">Crab (⭐88)</a> - A recommendation engine library for Python.</li>
</ul>

<ul>
<li><a href="https://github.com/maxsklar/BayesPy" rel="noopener noreferrer">BayesPy (⭐109)</a> - Bayesian Inference Tools in Python.</li>
</ul>

<ul>
<li><a href="https://github.com/GaelVaroquaux/scikit-learn-tutorial" rel="noopener noreferrer">scikit-learn tutorials (⭐132)</a> - Series of notebooks for learning scikit-learn.</li>
</ul>

<ul>
<li><a href="https://github.com/fabianp/group_lasso" rel="noopener noreferrer">group-lasso (⭐39)</a> - Some experiments with the coordinate descent algorithm used in the (Sparse) Group Lasso model.</li>
</ul>

<ul>
<li><a href="https://github.com/mne-tools/mne-python-notebooks" rel="noopener noreferrer">mne-python-notebooks (⭐29)</a> - IPython notebooks for EEG/MEG data processing using mne-python.</li>
</ul>

<ul>
<li><a href="https://github.com/NervanaSystems/neon_course" rel="noopener noreferrer">Neon Course (⭐93)</a> - IPython notebooks for a complete course around understanding Nervana's Neon.</li>
</ul>

<ul>
<li><a href="https://github.com/jvns/pandas-cookbook" rel="noopener noreferrer">pandas cookbook (⭐7.1k)</a> - Recipes for using Python's pandas library.</li>
</ul>

<ul>
<li><a href="https://github.com/BRML/climin" rel="noopener noreferrer">climin (⭐185)</a> - Optimization library focused on machine learning, pythonic implementations of gradient descent, LBFGS, rmsprop, adadelta and others.</li>
</ul>
<h3><p>Python / Kaggle Competition Source Code</p>
</h3>
<ul>
<li><a href="https://github.com/hammer/wikichallenge" rel="noopener noreferrer">wiki challenge (⭐11)</a> - An implementation of Dell Zhang's solution to Wikipedia's Participation Challenge on Kaggle.</li>
</ul>

<ul>
<li><a href="https://github.com/amueller/kaggle_insults" rel="noopener noreferrer">kaggle insults (⭐148)</a> - Kaggle Submission for "Detecting Insults in Social Commentary".</li>
</ul>

<ul>
<li><a href="https://github.com/MLWave/kaggle_acquire-valued-shoppers-challenge" rel="noopener noreferrer">kaggle_acquire-valued-shoppers-challenge (⭐66)</a> - Code for the Kaggle acquire valued shoppers challenge.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/kaggle-cifar" rel="noopener noreferrer">kaggle-cifar (⭐44)</a> - Code for the CIFAR-10 competition at Kaggle, uses cuda-convnet.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/kaggle-blackbox" rel="noopener noreferrer">kaggle-blackbox (⭐116)</a> - Deep learning made easy.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/kaggle-accelerometer" rel="noopener noreferrer">kaggle-accelerometer (⭐15)</a> - Code for Accelerometer Biometric Competition at Kaggle.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/kaggle-advertised-salaries" rel="noopener noreferrer">kaggle-advertised-salaries (⭐54)</a> - Predicting job salaries from ads - a Kaggle competition.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/kaggle-amazon" rel="noopener noreferrer">kaggle amazon (⭐25)</a> - Amazon access control challenge.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/kaggle-bestbuy_big" rel="noopener noreferrer">kaggle-bestbuy_big (⭐8)</a> - Code for the Best Buy competition at Kaggle.</li>
</ul>

<ul>
<li><a href="https://github.com/kastnerkyle/kaggle-dogs-vs-cats" rel="noopener noreferrer">Kaggle Dogs vs. Cats (⭐65)</a> - Code for Kaggle Dogs vs. Cats competition.</li>
</ul>

<ul>
<li><a href="https://github.com/benanne/kaggle-galaxies" rel="noopener noreferrer">Kaggle Galaxy Challenge (⭐498)</a> - Winning solution for the Galaxy Challenge on Kaggle.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/kaggle-gender" rel="noopener noreferrer">Kaggle Gender (⭐22)</a> - A Kaggle competition: discriminate gender based on handwriting.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/kaggle-merck" rel="noopener noreferrer">Kaggle Merck (⭐10)</a> - Merck challenge at Kaggle.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/kaggle-stackoverflow" rel="noopener noreferrer">Kaggle Stackoverflow (⭐44)</a> - Predicting closed questions on Stack Overflow.</li>
</ul>

<ul>
<li><a href="https://github.com/zygmuntz/wine-quality" rel="noopener noreferrer">wine-quality (⭐26)</a> - Predicting wine quality.</li>
</ul>
<h3><p>Ruby / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/ealdent/uea-stemmer" rel="noopener noreferrer">UEA Stemmer (⭐54)</a> - Ruby port of UEALite Stemmer - a conservative stemmer for search and indexing.</li>
</ul>
<h3><p>Ruby / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/arbox/machine-learning-with-ruby" rel="noopener noreferrer">Awesome Machine Learning with Ruby (⭐2.2k)</a> - Curated list of ML related resources for Ruby.</li>
</ul>

<ul>
<li><a href="https://github.com/febeling/rb-libsvm" rel="noopener noreferrer">rb-libsvm (⭐279)</a> - Ruby language bindings for LIBSVM which is a Library for Support Vector Machines.</li>
</ul>
<h3><p>Ruby / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/alexgutteridge/rsruby" rel="noopener noreferrer">rsruby (⭐334)</a> - Ruby - R bridge.</li>
</ul>
<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://cran.r-project.org/web/packages/biglasso/index.html" rel="noopener noreferrer">biglasso</a> - biglasso: Extending Lasso Model Fitting to Big Data in R.</li>
</ul>

<ul>
<li><a href="https://github.com/tqchen/xgboost/tree/master/R-package" rel="noopener noreferrer">XGBoost.R (⭐580)</a> - R binding for eXtreme Gradient Boosting (Tree) Library.</li>
</ul>
<h3><p>Scala / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/twitter/scalding" rel="noopener noreferrer">Scalding (⭐3.5k)</a> - A Scala API for Cascading.</li>
</ul>

<ul>
<li><a href="https://github.com/twitter/summingbird" rel="noopener noreferrer">Summing Bird (⭐2.1k)</a> - Streaming MapReduce with Scalding and Storm.</li>
</ul>

<ul>
<li><a href="https://github.com/twitter/algebird" rel="noopener noreferrer">Algebird (⭐2.3k)</a> - Abstract Algebra for Scala.</li>
</ul>
<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/etsy/Conjecture" rel="noopener noreferrer">Conjecture (⭐360)</a> - Scalable Machine Learning in Scalding.</li>
</ul>

<ul>
<li><a href="https://github.com/stripe/brushfire" rel="noopener noreferrer">brushfire (⭐391)</a> - Distributed decision tree ensemble learning in Scala.</li>
</ul>

<ul>
<li><a href="https://github.com/transcendent-ai-labs/DynaML" rel="noopener noreferrer">DynaML (⭐202)</a> - Scala Library/REPL for Machine Learning Research.</li>
</ul>
<h3><p>Swift / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/vlall/Swift-Brain" rel="noopener noreferrer">Swift Brain (⭐339)</a> - The first neural network / machine learning library written in Swift. This is a project for AI algorithms in Swift for iOS and OS X development. This project includes algorithms focused on Bayes theorem, neural networks, SVMs, Matrices, etc...</li>
</ul>
<h3><p>TensorFlow / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/jtoy/awesome-tensorflow" rel="noopener noreferrer">Awesome TensorFlow (⭐18k)</a> - A list of all things related to TensorFlow.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/44/"/>
    <summary>117 awesome projects updated on Oct 30 - Nov 05, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/42/</id>
    <title>Awesome Machine Learning Updates on Oct 16 - Oct 22, 2017</title>
    <updated>2017-10-22T07:12:32.000Z</updated>
    <published>2017-10-16T03:23:44.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Microsoft/CNTK" rel="noopener noreferrer">CNTK (⭐18k)</a> - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit. Documentation can be found <a href="https://docs.microsoft.com/cognitive-toolkit/" rel="noopener noreferrer">here</a>.</li>
</ul>
<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/jsmlt/jsmlt" rel="noopener noreferrer">JSMLT (⭐26)</a> - Machine learning toolkit with classification and clustering for Node.js; supports visualization (see <a href="https://visualml.io" rel="noopener noreferrer">visualml.io</a>).</li>
</ul>
<h3><p>JavaScript / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/stdlib-js/stdlib" rel="noopener noreferrer">stdlib (⭐5.8k)</a> - A standard library for JavaScript and Node.js, with an emphasis on numeric computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/42/"/>
    <summary>3 awesome projects updated on Oct 16 - Oct 22, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/41/</id>
    <title>Awesome Machine Learning Updates on Oct 09 - Oct 15, 2017</title>
    <updated>2017-10-10T19:37:39.000Z</updated>
    <published>2017-10-10T19:37:39.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://edwardlib.org/" rel="noopener noreferrer">Edward</a> - A library for probabilistic modelling, inference, and criticism. Built on top of TensorFlow.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/41/"/>
    <summary>1 awesome projects updated on Oct 09 - Oct 15, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/37/</id>
    <title>Awesome Machine Learning Updates on Sep 11 - Sep 17, 2017</title>
    <updated>2017-09-11T07:56:39.000Z</updated>
    <published>2017-09-11T07:56:39.000Z</published>
    <content type="html"><![CDATA[<h3><p>Swift / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/likedan/Awesome-CoreML-Models" rel="noopener noreferrer">Awesome Core ML Models (⭐7k)</a> - A curated list of machine learning models in CoreML format.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/37/"/>
    <summary>1 awesome projects updated on Sep 11 - Sep 17, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/33/</id>
    <title>Awesome Machine Learning Updates on Aug 14 - Aug 20, 2017</title>
    <updated>2017-08-19T21:01:36.000Z</updated>
    <published>2017-08-19T21:01:36.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/eriklindernoren/ML-From-Scratch" rel="noopener noreferrer">ML-From-Scratch (⭐31k)</a> - Implementations of Machine Learning models from scratch in Python with a focus on transparency. Aims to showcase the nuts and bolts of ML in an accessible way.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/33/"/>
    <summary>1 awesome projects updated on Aug 14 - Aug 20, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/32/</id>
    <title>Awesome Machine Learning Updates on Aug 07 - Aug 13, 2017</title>
    <updated>2017-08-09T10:24:50.000Z</updated>
    <published>2017-08-08T13:39:50.000Z</published>
    <content type="html"><![CDATA[<h3><p>Crystal / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/mathieulaporte/machine" rel="noopener noreferrer">machine (⭐40)</a> - Simple machine learning algorithm.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/pytorch/pytorch" rel="noopener noreferrer">PyTorch (⭐99k)</a> - Tensors and Dynamic neural networks in Python with strong GPU acceleration</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/32/"/>
    <summary>2 awesome projects updated on Aug 07 - Aug 13, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/31/</id>
    <title>Awesome Machine Learning Updates on Jul 31 - Aug 06, 2017</title>
    <updated>2017-07-31T02:52:39.000Z</updated>
    <published>2017-07-31T02:52:39.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/onyx-platform/onyx" rel="noopener noreferrer">Onyx (⭐2.1k)</a> - Distributed, masterless, high performance, fault tolerant data processing. Written entirely in Clojure.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/31/"/>
    <summary>1 awesome projects updated on Jul 31 - Aug 06, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/28/</id>
    <title>Awesome Machine Learning Updates on Jul 10 - Jul 16, 2017</title>
    <updated>2017-07-14T13:45:15.000Z</updated>
    <published>2017-07-14T13:45:15.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://www.dmtk.io/" rel="noopener noreferrer">Distributed Machine learning Tool Kit (DMTK)</a> - A distributed machine learning (parameter server) framework by Microsoft. Enables training models on large data sets across multiple machines. Current tools bundled with it include: LightLDA and Distributed (Multisense) Word Embedding.</li>
</ul>
<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/primaryobjects/lda" rel="noopener noreferrer">LDA.js (⭐294)</a> - LDA topic modelling for Node.js</li>
</ul>

<ul>
<li><a href="https://github.com/nicolaspanel/node-svm" rel="noopener noreferrer">Node-SVM (⭐301)</a> - Support Vector Machine for Node.js</li>
</ul>
<h3><p>JavaScript / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/simple-statistics/simple-statistics" rel="noopener noreferrer">simple-statistics (⭐3.5k)</a> - A JavaScript implementation of descriptive, regression, and inference statistics. Implemented in literate JavaScript with no dependencies, designed to work in all modern browsers (including IE) as well as in Node.js.</li>
</ul>
<h3><p>Matlab / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/josephmisiti/machine-learning-module" rel="noopener noreferrer">Machine Learning Module (⭐476)</a> - Class on machine w/ PDF, lectures, code</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/28/"/>
    <summary>5 awesome projects updated on Jul 10 - Jul 16, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/26/</id>
    <title>Awesome Machine Learning Updates on Jun 26 - Jul 02, 2017</title>
    <updated>2017-06-27T18:16:31.000Z</updated>
    <published>2017-06-27T18:16:31.000Z</published>
    <content type="html"><![CDATA[<h3><p>Swift / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/PerfectlySoft/Perfect-TensorFlow" rel="noopener noreferrer">Perfect TensorFlow (⭐167)</a> - Swift Language Bindings of TensorFlow. Using native TensorFlow models on both macOS / Linux.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/26/"/>
    <summary>1 awesome projects updated on Jun 26 - Jul 02, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/25/</id>
    <title>Awesome Machine Learning Updates on Jun 19 - Jun 25, 2017</title>
    <updated>2017-06-24T16:58:03.000Z</updated>
    <published>2017-06-24T16:58:03.000Z</published>
    <content type="html"><![CDATA[<h3><p>Ruby / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/arbox/nlp-with-ruby" rel="noopener noreferrer">Awesome NLP with Ruby (⭐1.1k)</a> - Curated link list for practical natural language processing in Ruby.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/25/"/>
    <summary>1 awesome projects updated on Jun 19 - Jun 25, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/23/</id>
    <title>Awesome Machine Learning Updates on Jun 05 - Jun 11, 2017</title>
    <updated>2017-06-05T12:52:48.000Z</updated>
    <published>2017-06-05T12:52:48.000Z</published>
    <content type="html"><![CDATA[<h3><p>Swift / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/xmartlabs/Bender" rel="noopener noreferrer">Bender (⭐1.8k)</a> - Fast Neural Networks framework built on top of Metal. Supports TensorFlow models.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/23/"/>
    <summary>1 awesome projects updated on Jun 05 - Jun 11, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/22/</id>
    <title>Awesome Machine Learning Updates on May 29 - Jun 04, 2017</title>
    <updated>2017-05-30T13:40:21.000Z</updated>
    <published>2017-05-30T13:37:35.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://d3js.org/" rel="noopener noreferrer">D3.js</a></li>
</ul>

<ul>
<li><a href="http://learnjsdata.com/" rel="noopener noreferrer">Learn JS Data</a></li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/22/"/>
    <summary>2 awesome projects updated on May 29 - Jun 04, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/21/</id>
    <title>Awesome Machine Learning Updates on May 22 - May 28, 2017</title>
    <updated>2017-05-23T19:16:38.000Z</updated>
    <published>2017-05-22T12:18:25.000Z</published>
    <content type="html"><![CDATA[<h3><p>Go / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/ynqa/word-embedding" rel="noopener noreferrer">word-embedding (⭐506)</a> - Word Embeddings: the full implementation of word2vec, GloVe in Go.</li>
</ul>
<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://www.amidsttoolbox.com/" rel="noopener noreferrer">AMIDST Toolbox</a> - A Java Toolbox for Scalable Probabilistic Machine Learning.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/21/"/>
    <summary>2 awesome projects updated on May 22 - May 28, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/20/</id>
    <title>Awesome Machine Learning Updates on May 15 - May 21, 2017</title>
    <updated>2017-05-19T18:01:37.000Z</updated>
    <published>2017-05-19T17:39:47.000Z</published>
    <content type="html"><![CDATA[<h3><p>General-Purpose Machine Learning / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/apache/incubator-mxnet/tree/master/perl-package" rel="noopener noreferrer">MXnet for Deep Learning, in Perl (⭐21k)</a>,
also <a href="https://metacpan.org/pod/AI::MXNet" rel="noopener noreferrer">released in CPAN</a>.</li>
</ul>
<h3><p>Perl 6 / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/titsuki/p6-Algorithm-NaiveBayes" rel="noopener noreferrer">Naïve Bayes (⭐3)</a></li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/20/"/>
    <summary>2 awesome projects updated on May 15 - May 21, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/19/</id>
    <title>Awesome Machine Learning Updates on May 08 - May 14, 2017</title>
    <updated>2017-05-13T05:00:56.000Z</updated>
    <published>2017-05-13T05:00:56.000Z</published>
    <content type="html"><![CDATA[<h3><p>Scala / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/Workday/upshot-montague" rel="noopener noreferrer">Montague (⭐59)</a> - Montague is a semantic parsing library for Scala with an easy-to-use DSL.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/19/"/>
    <summary>1 awesome projects updated on May 08 - May 14, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/18/</id>
    <title>Awesome Machine Learning Updates on May 01 - May 07, 2017</title>
    <updated>2017-05-04T17:51:19.000Z</updated>
    <published>2017-05-04T17:51:19.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/karpathy/neuraltalk" rel="noopener noreferrer">NeuralTalk (⭐5.5k)</a> - NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.</li>
</ul>
<h3><p>Python / Reinforcement Learning</p>
</h3>
<ul>
<li><a href="https://github.com/deepmind/lab" rel="noopener noreferrer">DeepMind Lab (⭐7.4k)</a> - DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software. Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning.</li>
</ul>

<ul>
<li><a href="https://github.com/mwydmuch/ViZDoom" rel="noopener noreferrer">ViZDoom (⭐2k)</a> - ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is primarily intended for research in machine visual learning, and deep reinforcement learning, in particular.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/18/"/>
    <summary>3 awesome projects updated on May 01 - May 07, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/17/</id>
    <title>Awesome Machine Learning Updates on Apr 24 - Apr 30, 2017</title>
    <updated>2017-04-27T21:10:54.000Z</updated>
    <published>2017-04-27T21:10:54.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/jwkvam/bowtie" rel="noopener noreferrer">Bowtie (⭐768)</a> - A dashboard library for interactive visualizations using flask socketio and react.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/17/"/>
    <summary>1 awesome projects updated on Apr 24 - Apr 30, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/15/</id>
    <title>Awesome Machine Learning Updates on Apr 10 - Apr 16, 2017</title>
    <updated>2017-04-13T12:17:22.000Z</updated>
    <published>2017-04-13T12:17:22.000Z</published>
    <content type="html"><![CDATA[<h3><p>General-Purpose Machine Learning / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/LaurentMazare/tensorflow-ocaml" rel="noopener noreferrer">TensorFlow (⭐287)</a> - OCaml bindings for TensorFlow.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/15/"/>
    <summary>1 awesome projects updated on Apr 10 - Apr 16, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/13/</id>
    <title>Awesome Machine Learning Updates on Mar 27 - Apr 02, 2017</title>
    <updated>2017-03-27T12:32:21.000Z</updated>
    <published>2017-03-27T12:32:21.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/williamFalcon/pix2pix-keras" rel="noopener noreferrer">Image-to-Image Translation with Conditional Adversarial Networks (⭐143)</a> - Implementation of image to image (pix2pix) translation from the paper by <a href="https://arxiv.org/pdf/1611.07004.pdf" rel="noopener noreferrer">isola et al</a>.[DEEP LEARNING]</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/13/"/>
    <summary>1 awesome projects updated on Mar 27 - Apr 02, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/10/</id>
    <title>Awesome Machine Learning Updates on Mar 06 - Mar 12, 2017</title>
    <updated>2017-03-09T03:05:19.000Z</updated>
    <published>2017-03-09T03:05:19.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/fukuball/fuku-ml" rel="noopener noreferrer">fuku-ml (⭐284)</a> - Simple machine learning library, including Perceptron, Regression, Support Vector Machine, Decision Tree and more, it's easy to use and easy to learn for beginners.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/10/"/>
    <summary>1 awesome projects updated on Mar 06 - Mar 12, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/8/</id>
    <title>Awesome Machine Learning Updates on Feb 20 - Feb 26, 2017</title>
    <updated>2017-02-22T16:39:31.000Z</updated>
    <published>2017-02-22T16:39:31.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/reiinakano/scikit-plot" rel="noopener noreferrer">scikit-plot (⭐2.4k)</a> - A visualization library for quick and easy generation of common plots in data analysis and machine learning.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/8/"/>
    <summary>1 awesome projects updated on Feb 20 - Feb 26, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/7/</id>
    <title>Awesome Machine Learning Updates on Feb 13 - Feb 19, 2017</title>
    <updated>2017-02-13T11:26:41.000Z</updated>
    <published>2017-02-13T11:26:41.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://mldb.ai" rel="noopener noreferrer">MLDB</a> - The Machine Learning Database is a database designed for machine learning. Send it commands over a RESTful API to store data, explore it using SQL, then train machine learning models and expose them as APIs.</li>
</ul>

<ul>
<li><a href="https://code.google.com/archive/p/sofia-ml" rel="noopener noreferrer">sofia-ml</a> - Suite of fast incremental algorithms.</li>
</ul>

<ul>
<li><a href="https://languagemachines.github.io/timbl/" rel="noopener noreferrer">Timbl</a> - A software package/C++ library implementing several memory-based learning algorithms, among which IB1-IG, an implementation of k-nearest neighbor classification, and IGTree, a decision-tree approximation of IB1-IG. Commonly used for NLP.</li>
</ul>
<h3><p>C++ / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/LanguageMachines/frog" rel="noopener noreferrer">frog (⭐80)</a> - Memory-based NLP suite developed for Dutch: PoS tagger, lemmatiser, dependency parser, NER, shallow parser, morphological analyzer.</li>
</ul>

<ul>
<li><a href="https://github.com/LanguageMachines/ucto" rel="noopener noreferrer">ucto (⭐70)</a> - Unicode-aware regular-expression based tokenizer for various languages. Tool and C++ library. Supports FoLiA format.</li>
</ul>
<h3><p>C++ / Speech Recognition</p>
</h3>
<ul>
<li><a href="https://github.com/kaldi-asr/kaldi" rel="noopener noreferrer">Kaldi (⭐15k)</a> - Kaldi is a toolkit for speech recognition written in C++ and licensed under the Apache License v2.0. Kaldi is intended for use by speech recognition researchers.</li>
</ul>
<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://elki-project.github.io/" rel="noopener noreferrer">ELKI</a> - Java toolkit for data mining. (unsupervised: clustering, outlier detection etc.)</li>
</ul>
<h3><p>JavaScript / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.amcharts.com/" rel="noopener noreferrer">amCharts</a></li>
</ul>
<h3><p>Julia / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/GiovineItalia/Gadfly.jl" rel="noopener noreferrer">Gadfly (⭐1.9k)</a> - Crafty statistical graphics for Julia.</li>
</ul>
<h3><p>Lua / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://scilua.org/" rel="noopener noreferrer">SciLua</a></li>
</ul>
<h3><p>.NET / Computer Vision</p>
</h3>
<ul>
<li><a href="https://code.google.com/archive/p/opencvdotnet" rel="noopener noreferrer">OpenCVDotNet</a> - A wrapper for the OpenCV project to be used with .NET applications.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="http://textblob.readthedocs.io/en/dev/" rel="noopener noreferrer">TextBlob</a> - Providing a consistent API for diving into common natural language processing (NLP) tasks. Stands on the giant shoulders of NLTK and Pattern, and plays nicely with both.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://turi.com/products/create/docs/" rel="noopener noreferrer">graphlab-create</a> - A library with various machine learning models (regression, clustering, recommender systems, graph analytics, etc.) implemented on top of a disk-backed DataFrame.</li>
</ul>

<ul>
<li><a href="https://github.com/RaRe-Technologies/gensim" rel="noopener noreferrer">gensim (⭐16k)</a> - Topic Modelling for Humans.</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/mikedewar/d3py" rel="noopener noreferrer">d3py (⭐1.4k)</a> - A plotting library for Python, based on <a href="https://d3js.org/" rel="noopener noreferrer">D3.js</a>.</li>
</ul>

<ul>
<li><a href="http://pygal.org/en/stable/" rel="noopener noreferrer">pygal</a> - A Python SVG Charts Creator.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="http://optunity.readthedocs.io/en/latest/notebooks/index.html" rel="noopener noreferrer">Optunity examples</a> - Examples demonstrating how to use Optunity in synergy with machine learning libraries.</li>
</ul>
<h3><p>Ruby / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/kevincobain2000/listof" rel="noopener noreferrer">Listof (⭐30)</a> - Community based data collection, packed in gem. Get list of pretty much anything (stop words, countries, non words) in txt, JSON or hash. <a href="http://kevincobain2000.github.io/listof/" rel="noopener noreferrer">Demo/Search for a list</a></li>
</ul>
<h3><p>SAS / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://www.sas.com/en_us/software/enterprise-miner.html" rel="noopener noreferrer">Enterprise Miner</a> - Data mining and machine learning that creates deployable models using a GUI or code.</li>
</ul>

<ul>
<li><a href="https://www.sas.com/en_us/software/factory-miner.html" rel="noopener noreferrer">Factory Miner</a> - Automatically creates deployable machine learning models across numerous market or customer segments using a GUI.</li>
</ul>
<h3><p>SAS / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://www.sas.com/en_us/software/university-edition.html" rel="noopener noreferrer">University Edition</a> - FREE! Includes all SAS packages necessary for data analysis and visualization, and includes online SAS courses.</li>
</ul>
<h3><p>SAS / Demos and Scripts</p>
</h3>
<ul>
<li><a href="https://github.com/sassoftware/enlighten-apply/tree/master/ML_tables" rel="noopener noreferrer">ML_Tables (⭐130)</a> - Concise cheat sheets containing machine learning best practices.</li>
</ul>

<ul>
<li><a href="https://github.com/sassoftware/enlighten-apply" rel="noopener noreferrer">enlighten-apply (⭐130)</a> - Example code and materials that illustrate applications of SAS machine learning techniques.</li>
</ul>

<ul>
<li><a href="https://github.com/sassoftware/enlighten-integration" rel="noopener noreferrer">enlighten-integration</a> - Example code and materials that illustrate techniques for integrating SAS with other analytics technologies in Java, PMML, Python and R.</li>
</ul>

<ul>
<li><a href="https://github.com/sassoftware/enlighten-deep" rel="noopener noreferrer">enlighten-deep</a> - Example code and materials that illustrate using neural networks with several hidden layers in SAS.</li>
</ul>

<ul>
<li><a href="https://github.com/sassoftware/dm-flow" rel="noopener noreferrer">dm-flow</a> - Library of SAS Enterprise Miner process flow diagrams to help you learn by example about specific data mining topics.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/7/"/>
    <summary>26 awesome projects updated on Feb 13 - Feb 19, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/5/</id>
    <title>Awesome Machine Learning Updates on Jan 30 - Feb 05, 2017</title>
    <updated>2017-02-03T07:32:30.000Z</updated>
    <published>2017-02-03T07:32:30.000Z</published>
    <content type="html"><![CDATA[<h3><p>Scala / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/Hydrospheredata/mist" rel="noopener noreferrer">Hydrosphere Mist (⭐325)</a> - a service for deployment Apache Spark MLLib machine learning models as realtime, batch or reactive web services.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/5/"/>
    <summary>1 awesome projects updated on Jan 30 - Feb 05, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2017/1/</id>
    <title>Awesome Machine Learning Updates on Jan 02 - Jan 08, 2017</title>
    <updated>2017-01-04T12:31:07.000Z</updated>
    <published>2017-01-04T12:31:07.000Z</published>
    <content type="html"><![CDATA[<h3><p>Go / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/tebeka/snowball" rel="noopener noreferrer">snowball (⭐48)</a> - Snowball Stemmer for Go.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2017/1/"/>
    <summary>1 awesome projects updated on Jan 02 - Jan 08, 2017</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/51/</id>
    <title>Awesome Machine Learning Updates on Dec 19 - Dec 25, 2016</title>
    <updated>2016-12-20T04:45:47.000Z</updated>
    <published>2016-12-20T04:45:47.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Neural Networks</p>
</h3>
<ul>
<li><a href="https://github.com/atmb4u/data-driven-code" rel="noopener noreferrer">Data Driven Code (⭐30)</a> - Very simple implementation of neural networks for dummies in python without using any libraries, with detailed comments.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/51/"/>
    <summary>1 awesome projects updated on Dec 19 - Dec 25, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/46/</id>
    <title>Awesome Machine Learning Updates on Nov 14 - Nov 20, 2016</title>
    <updated>2016-11-19T17:31:34.000Z</updated>
    <published>2016-11-19T17:31:34.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/peterwittek/somoclu" rel="noopener noreferrer">somoclu (⭐277)</a> Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters, has python API.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/46/"/>
    <summary>1 awesome projects updated on Nov 14 - Nov 20, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/43/</id>
    <title>Awesome Machine Learning Updates on Oct 24 - Oct 30, 2016</title>
    <updated>2016-10-29T10:20:38.000Z</updated>
    <published>2016-10-29T10:13:48.000Z</published>
    <content type="html"><![CDATA[<h3><p>C / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/GHamrouni/Recommender" rel="noopener noreferrer">Recommender (⭐268)</a> - A C library for product recommendations/suggestions using collaborative filtering (CF).</li>
</ul>
<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://code.google.com/p/cuda-convnet/" rel="noopener noreferrer">CUDA</a> - This is a fast C++/CUDA implementation of convolutional [DEEP LEARNING]</li>
</ul>

<ul>
<li><a href="https://github.com/clab/dynet" rel="noopener noreferrer">DyNet (⭐3.4k)</a> - A dynamic neural network library working well with networks that have dynamic structures that change for every training instance. Written in C++ with bindings in Python.</li>
</ul>

<ul>
<li><a href="https://github.com/FidoProject/Fido" rel="noopener noreferrer">Fido (⭐462)</a> - A highly-modular C++ machine learning library for embedded electronics and robotics.</li>
</ul>

<ul>
<li><a href="https://github.com/Microsoft/LightGBM" rel="noopener noreferrer">LightGBM (⭐18k)</a> - Microsoft's fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.</li>
</ul>

<ul>
<li><a href="https://root.cern.ch" rel="noopener noreferrer">ROOT</a> - A modular scientific software framework. It provides all the functionalities needed to deal with big data processing, statistical analysis, visualization and storage.</li>
</ul>

<ul>
<li><a href="http://image.diku.dk/shark/sphinx_pages/build/html/index.html" rel="noopener noreferrer">shark</a> - A fast, modular, feature-rich open-source C++ machine learning library.</li>
</ul>
<h3><p>C++ / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/mit-nlp/MITIE" rel="noopener noreferrer">MIT Information Extraction Toolkit (⭐3k)</a> - C, C++, and Python tools for named entity recognition and relation extraction</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/43/"/>
    <summary>8 awesome projects updated on Oct 24 - Oct 30, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/42/</id>
    <title>Awesome Machine Learning Updates on Oct 17 - Oct 23, 2016</title>
    <updated>2016-10-19T19:29:43.000Z</updated>
    <published>2016-10-17T16:26:51.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/D3xterjs/pydexter" rel="noopener noreferrer">PyDexter (⭐30)</a> - Simple plotting for Python. Wrapper for D3xterjs; easily render charts in-browser.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/kendricktan/suiron/" rel="noopener noreferrer">Suiron (⭐708)</a> - Machine Learning for RC Cars.</li>
</ul>
<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Azure/Azure-TDSP-Utilities" rel="noopener noreferrer">TDSP-Utilities (⭐378)</a> - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modelling and Reporting (AMR).</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/42/"/>
    <summary>3 awesome projects updated on Oct 17 - Oct 23, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/34/</id>
    <title>Awesome Machine Learning Updates on Aug 22 - Aug 28, 2016</title>
    <updated>2016-08-22T22:53:19.000Z</updated>
    <published>2016-08-22T22:53:19.000Z</published>
    <content type="html"><![CDATA[<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/valdanylchuk/swiftlearner/" rel="noopener noreferrer">SwiftLearner (⭐40)</a> - Simply written algorithms to help study ML or write your own implementations.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/34/"/>
    <summary>1 awesome projects updated on Aug 22 - Aug 28, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/32/</id>
    <title>Awesome Machine Learning Updates on Aug 08 - Aug 14, 2016</title>
    <updated>2016-08-11T19:31:59.000Z</updated>
    <published>2016-08-11T19:31:59.000Z</published>
    <content type="html"><![CDATA[<h3><p>Swift / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Somnibyte/MLKit" rel="noopener noreferrer">MLKit (⭐153)</a> - A simple Machine Learning Framework written in Swift. Currently features Simple Linear Regression, Polynomial Regression, and Ridge Regression.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/32/"/>
    <summary>1 awesome projects updated on Aug 08 - Aug 14, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/31/</id>
    <title>Awesome Machine Learning Updates on Aug 01 - Aug 07, 2016</title>
    <updated>2016-08-05T05:24:12.000Z</updated>
    <published>2016-08-05T05:24:12.000Z</published>
    <content type="html"><![CDATA[<h3><p>Elixir / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/fredwu/simple_bayes" rel="noopener noreferrer">Simple Bayes (⭐396)</a> - A Simple Bayes / Naive Bayes implementation in Elixir.</li>
</ul>
<h3><p>Elixir / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/fredwu/stemmer" rel="noopener noreferrer">Stemmer (⭐154)</a> - An English (Porter2) stemming implementation in Elixir.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/31/"/>
    <summary>2 awesome projects updated on Aug 01 - Aug 07, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/27/</id>
    <title>Awesome Machine Learning Updates on Jul 04 - Jul 10, 2016</title>
    <updated>2016-07-09T20:12:31.000Z</updated>
    <published>2016-07-09T20:12:31.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/Lasagne/Lasagne" rel="noopener noreferrer">Lasagne (⭐3.9k)</a> - Lightweight library to build and train neural networks in Theano.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/27/"/>
    <summary>1 awesome projects updated on Jul 04 - Jul 10, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/26/</id>
    <title>Awesome Machine Learning Updates on Jun 27 - Jul 03, 2016</title>
    <updated>2016-07-01T16:31:02.000Z</updated>
    <published>2016-07-01T16:31:02.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/justmarkham/scikit-learn-videos" rel="noopener noreferrer">Introduction to machine learning with scikit-learn (⭐3.8k)</a> - IPython notebooks from Data School's video tutorials on scikit-learn.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/26/"/>
    <summary>1 awesome projects updated on Jun 27 - Jul 03, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/25/</id>
    <title>Awesome Machine Learning Updates on Jun 20 - Jun 26, 2016</title>
    <updated>2016-06-22T17:55:43.000Z</updated>
    <published>2016-06-21T13:41:45.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/jamesturk/jellyfish" rel="noopener noreferrer">jellyfish (⭐2.2k)</a> - a python library for doing approximate and phonetic matching of strings.</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/sevamoo/SOMPY" rel="noopener noreferrer">SOMPY (⭐551)</a> - Self Organizing Map written in Python (Uses neural networks for data analysis).</li>
</ul>

<ul>
<li><a href="https://github.com/lmcinnes/hdbscan" rel="noopener noreferrer">HDBScan (⭐102)</a> - implementation of the hdbscan algorithm in Python - used for clustering</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/25/"/>
    <summary>3 awesome projects updated on Jun 20 - Jun 26, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/19/</id>
    <title>Awesome Machine Learning Updates on May 09 - May 15, 2016</title>
    <updated>2016-05-13T09:03:37.000Z</updated>
    <published>2016-05-11T02:02:19.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/amznlabs/amazon-dsstne" rel="noopener noreferrer">DSSTNE (⭐4.4k)</a> - A software library created by Amazon for training and deploying deep neural networks using GPUs which emphasizes speed and scale over experimental flexibility.</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/nathanepstein/dora" rel="noopener noreferrer">Dora (⭐649)</a> - Tools for exploratory data analysis in Python.</li>
</ul>

<ul>
<li><a href="http://www.ruffus.org.uk" rel="noopener noreferrer">Ruffus</a> - Computation Pipeline library for python.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/19/"/>
    <summary>3 awesome projects updated on May 09 - May 15, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/17/</id>
    <title>Awesome Machine Learning Updates on Apr 25 - May 01, 2016</title>
    <updated>2016-04-25T15:00:01.000Z</updated>
    <published>2016-04-25T15:00:01.000Z</published>
    <content type="html"><![CDATA[<h3><p>Scala / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="http://spark-notebook.io" rel="noopener noreferrer">Spark Notebook</a> - Interactive and Reactive Data Science using Scala and Spark.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/17/"/>
    <summary>1 awesome projects updated on Apr 25 - May 01, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/13/</id>
    <title>Awesome Machine Learning Updates on Mar 28 - Apr 03, 2016</title>
    <updated>2016-04-01T03:39:42.000Z</updated>
    <published>2016-04-01T03:39:42.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/tflearn/tflearn" rel="noopener noreferrer">TFLearn (⭐9.6k)</a> - Deep learning library featuring a higher-level API for TensorFlow.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/13/"/>
    <summary>1 awesome projects updated on Mar 28 - Apr 03, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/11/</id>
    <title>Awesome Machine Learning Updates on Mar 14 - Mar 20, 2016</title>
    <updated>2016-03-18T10:55:44.000Z</updated>
    <published>2016-03-18T10:55:44.000Z</published>
    <content type="html"><![CDATA[<h3><p>C / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/pjreddie/darknet" rel="noopener noreferrer">Darknet (⭐26k)</a> - Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/11/"/>
    <summary>1 awesome projects updated on Mar 14 - Mar 20, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/7/</id>
    <title>Awesome Machine Learning Updates on Feb 15 - Feb 21, 2016</title>
    <updated>2016-02-16T00:20:47.000Z</updated>
    <published>2016-02-16T00:20:47.000Z</published>
    <content type="html"><![CDATA[<h3><p>Rust / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/AtheMathmo/rusty-machine" rel="noopener noreferrer">rusty-machine (⭐1.3k)</a> - a pure-rust machine learning library.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/7/"/>
    <summary>1 awesome projects updated on Feb 15 - Feb 21, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/5/</id>
    <title>Awesome Machine Learning Updates on Feb 01 - Feb 07, 2016</title>
    <updated>2016-02-05T02:56:13.000Z</updated>
    <published>2016-02-04T12:17:05.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://samoa.incubator.apache.org/" rel="noopener noreferrer">Samoa</a> SAMOA is a framework that includes distributed machine learning for data streams with an interface to plug-in different stream processing platforms.</li>
</ul>
<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/harthur/brain" rel="noopener noreferrer">Brain (⭐8k)</a> - Neural networks in JavaScript <strong>[Deprecated]</strong></li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/IDSIA/brainstorm" rel="noopener noreferrer">Brainstorm (⭐1.3k)</a> - Fast, flexible and fun neural networks. This is the successor of PyBrain.</li>
</ul>
<h3><p>Rust / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/tedsta/deeplearn-rs" rel="noopener noreferrer">deeplearn-rs (⭐210)</a> - deeplearn-rs provides simple networks that use matrix multiplication, addition, and ReLU under the MIT license.</li>
</ul>

<ul>
<li><a href="https://github.com/maciejkula/rustlearn" rel="noopener noreferrer">rustlearn (⭐639)</a> - a machine learning framework featuring logistic regression, support vector machines, decision trees and random forests.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/5/"/>
    <summary>5 awesome projects updated on Feb 01 - Feb 07, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/3/</id>
    <title>Awesome Machine Learning Updates on Jan 18 - Jan 24, 2016</title>
    <updated>2016-01-23T15:38:11.000Z</updated>
    <published>2016-01-18T02:02:28.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/baidu-research/warp-ctc" rel="noopener noreferrer">Warp-CTC (⭐4.1k)</a> - A fast parallel implementation of Connectionist Temporal Classification (CTC), on both CPU and GPU.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://cmusatyalab.github.io/openface/" rel="noopener noreferrer">OpenFace</a> - Free and open source face recognition with deep neural networks.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/3/"/>
    <summary>2 awesome projects updated on Jan 18 - Jan 24, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2016/2/</id>
    <title>Awesome Machine Learning Updates on Jan 11 - Jan 17, 2016</title>
    <updated>2016-01-13T08:48:03.000Z</updated>
    <published>2016-01-13T08:48:03.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/NVIDIA/DIGITS" rel="noopener noreferrer">DIGITS (⭐4.2k)</a> - The Deep Learning GPU Training System (DIGITS) is a web application for training deep learning models.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2016/2/"/>
    <summary>1 awesome projects updated on Jan 11 - Jan 17, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/53/</id>
    <title>Awesome Machine Learning Updates on Jan 04 - Jan 10, 2016</title>
    <updated>2016-01-03T12:32:17.000Z</updated>
    <published>2016-01-02T17:14:39.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / Gesture Detection</p>
</h3>
<ul>
<li><a href="https://github.com/nickgillian/grt" rel="noopener noreferrer">grt (⭐888)</a> - The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, C++ machine learning library designed for real-time gesture recognition.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/pgmpy/pgmpy" rel="noopener noreferrer">pgmpy (⭐3.3k)</a> A python library for working with Probabilistic Graphical Models.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/53/"/>
    <summary>2 awesome projects updated on Jan 04 - Jan 10, 2016</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/51/</id>
    <title>Awesome Machine Learning Updates on Dec 21 - Dec 27, 2015</title>
    <updated>2015-12-17T11:00:58.000Z</updated>
    <published>2015-12-15T18:50:26.000Z</published>
    <content type="html"><![CDATA[<h3><p>Natural Language Processing / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/fukuball/jieba-php" rel="noopener noreferrer">jieba-php (⭐1.4k)</a> - Chinese Words Segmentation Utilities.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/scikit-image/scikit-image" rel="noopener noreferrer">Scikit-Image (⭐6.5k)</a> - A collection of algorithms for image processing in Python.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/ericjang/tdb" rel="noopener noreferrer">TDB (⭐1.4k)</a> - TensorDebugger (TDB) is a visual debugger for deep learning. It features interactive, node-by-node debugging and visualization for TensorFlow.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/51/"/>
    <summary>3 awesome projects updated on Dec 21 - Dec 27, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/50/</id>
    <title>Awesome Machine Learning Updates on Dec 14 - Dec 20, 2015</title>
    <updated>2015-12-13T14:52:13.000Z</updated>
    <published>2015-12-13T14:52:13.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/airbnb/aerosolve" rel="noopener noreferrer">aerosolve (⭐4.8k)</a> - A machine learning library by Airbnb designed from the ground up to be human friendly.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/50/"/>
    <summary>1 awesome projects updated on Dec 14 - Dec 20, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/48/</id>
    <title>Awesome Machine Learning Updates on Nov 30 - Dec 06, 2015</title>
    <updated>2015-11-24T04:20:04.000Z</updated>
    <published>2015-11-24T04:20:04.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/sinhrks/ggfortify" rel="noopener noreferrer">ggfortify (⭐539)</a> - Unified interface to ggplot2 popular R packages.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/48/"/>
    <summary>1 awesome projects updated on Nov 30 - Dec 06, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/46/</id>
    <title>Awesome Machine Learning Updates on Nov 16 - Nov 22, 2015</title>
    <updated>2015-11-15T21:00:57.000Z</updated>
    <published>2015-11-11T20:03:45.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/nathanepstein/datakit" rel="noopener noreferrer">datakit (⭐287)</a> - A lightweight framework for data analysis in JavaScript</li>
</ul>
<h3><p>Matlab / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/PRML/PRMLT" rel="noopener noreferrer">Pattern Recognition and Machine Learning (⭐6.2k)</a> - This package contains the matlab implementation of the algorithms described in the book Pattern Recognition and Machine Learning by C. Bishop.</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/bokeh/bokeh" rel="noopener noreferrer">bokeh (⭐20k)</a> - Interactive Web Plotting for Python.</li>
</ul>

<ul>
<li><a href="https://plot.ly/python/" rel="noopener noreferrer">plotly</a> - Collaborative web plotting for Python and matplotlib.</li>
</ul>

<ul>
<li><a href="https://github.com/blaze/blaze" rel="noopener noreferrer">Blaze (⭐3.2k)</a> - NumPy and Pandas interface to Big Data.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/dib-lab/2012-paper-diginorm" rel="noopener noreferrer">2012-paper-diginorm (⭐8)</a></li>
</ul>

<ul>
<li><a href="https://github.com/hangtwenty/dive-into-machine-learning" rel="noopener noreferrer">Dive into Machine Learning  with Python Jupyter notebook and scikit-learn (⭐11k)</a> - "I learned Python by hacking first, and getting serious <em>later.</em> I wanted to do this with Machine Learning. If this is your style, join me in getting a bit ahead of yourself."</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/46/"/>
    <summary>7 awesome projects updated on Nov 16 - Nov 22, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/42/</id>
    <title>Awesome Machine Learning Updates on Oct 19 - Oct 25, 2015</title>
    <updated>2015-10-18T03:11:52.000Z</updated>
    <published>2015-10-18T03:11:52.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/donnemartin/data-science-ipython-notebooks" rel="noopener noreferrer">data-science-ipython-notebooks (⭐29k)</a> - Continually updated Data Science Python Notebooks: Spark, Hadoop MapReduce, HDFS, AWS, Kaggle, scikit-learn, matplotlib, pandas, NumPy, SciPy, and various command lines.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/42/"/>
    <summary>1 awesome projects updated on Oct 19 - Oct 25, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/39/</id>
    <title>Awesome Machine Learning Updates on Sep 28 - Oct 04, 2015</title>
    <updated>2015-09-27T03:59:43.000Z</updated>
    <published>2015-09-27T03:59:43.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/mljs/ml" rel="noopener noreferrer">ml.js (⭐2.7k)</a> - Machine learning and numerical analysis tools for Node.js and the Browser!</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/39/"/>
    <summary>1 awesome projects updated on Sep 28 - Oct 04, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/35/</id>
    <title>Awesome Machine Learning Updates on Aug 31 - Sep 06, 2015</title>
    <updated>2015-08-28T13:35:51.000Z</updated>
    <published>2015-08-24T18:04:03.000Z</published>
    <content type="html"><![CDATA[<h3><p>General-Purpose Machine Learning / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/yconst/YCML" rel="noopener noreferrer">YCML (⭐117)</a> - A Machine Learning framework for Objective-C and Swift (OS X / iOS).</li>
</ul>

<ul>
<li><a href="https://github.com/denissimon/prediction-builder" rel="noopener noreferrer">PredictionBuilder (⭐114)</a> - A library for machine learning that builds predictions using a linear regression.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/35/"/>
    <summary>2 awesome projects updated on Aug 31 - Sep 06, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/34/</id>
    <title>Awesome Machine Learning Updates on Aug 24 - Aug 30, 2015</title>
    <updated>2015-08-22T14:59:50.000Z</updated>
    <published>2015-08-22T14:59:50.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="http://konlpy.org" rel="noopener noreferrer">KoNLPy</a> - A Python package for Korean natural language processing.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/34/"/>
    <summary>1 awesome projects updated on Aug 24 - Aug 30, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/31/</id>
    <title>Awesome Machine Learning Updates on Aug 03 - Aug 09, 2015</title>
    <updated>2015-07-27T00:21:47.000Z</updated>
    <published>2015-07-27T00:21:47.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/h2oai/h2o-3" rel="noopener noreferrer">H2O (⭐7.5k)</a> - ML engine that supports distributed learning on Hadoop, Spark or your laptop via APIs in R, Python, Scala, REST/JSON.</li>
</ul>
<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/h2oai/sparkling-water" rel="noopener noreferrer">H2O Sparkling Water (⭐977)</a> - H2O and Spark interoperability.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/31/"/>
    <summary>2 awesome projects updated on Aug 03 - Aug 09, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/25/</id>
    <title>Awesome Machine Learning Updates on Jun 22 - Jun 28, 2015</title>
    <updated>2015-06-21T13:30:28.000Z</updated>
    <published>2015-06-20T10:44:00.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/meta-toolkit/meta" rel="noopener noreferrer">MeTA (⭐713)</a> - <a href="https://meta-toolkit.org/" rel="noopener noreferrer">MeTA : ModErn Text Analysis</a> is a C++ Data Sciences Toolkit that facilitates mining big text data.</li>
</ul>
<h3><p>JavaScript / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="http://sigmajs.org/" rel="noopener noreferrer">Sigma.js</a> - JavaScript library dedicated to graph drawing.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="https://github.com/ukoethe/vigra" rel="noopener noreferrer">Vigranumpy (⭐438)</a> - Python bindings for the VIGRA C++ computer vision library.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/25/"/>
    <summary>3 awesome projects updated on Jun 22 - Jun 28, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/18/</id>
    <title>Awesome Machine Learning Updates on May 04 - May 10, 2015</title>
    <updated>2015-05-02T09:41:18.000Z</updated>
    <published>2015-05-02T09:41:18.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/rasbt/mlxtend" rel="noopener noreferrer">mlxtend (⭐5.1k)</a> - A library consisting of useful tools for data science and machine learning tasks.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/18/"/>
    <summary>1 awesome projects updated on May 04 - May 10, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/17/</id>
    <title>Awesome Machine Learning Updates on Apr 27 - May 03, 2015</title>
    <updated>2015-04-21T06:58:23.000Z</updated>
    <published>2015-04-21T06:58:23.000Z</published>
    <content type="html"><![CDATA[<h3><p>General-Purpose Machine Learning / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/gianlucabertani/MAChineLearning" rel="noopener noreferrer">MAChineLearning (⭐37)</a> - An Objective-C multilayer perceptron library, with full support for training through backpropagation. Implemented using vDSP and vecLib, it's 20 times faster than its Java equivalent. Includes sample code for use from Swift.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/17/"/>
    <summary>1 awesome projects updated on Apr 27 - May 03, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/15/</id>
    <title>Awesome Machine Learning Updates on Apr 13 - Apr 19, 2015</title>
    <updated>2015-04-09T18:07:48.000Z</updated>
    <published>2015-04-09T14:17:48.000Z</published>
    <content type="html"><![CDATA[<h3><p>JavaScript / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/Tom-Alexander/regression-js" rel="noopener noreferrer">regression-js (⭐951)</a> - A javascript library containing a collection of least squares fitting methods for finding a trend in a set of data.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/mwgg/GreatCircle" rel="noopener noreferrer">GreatCircle (⭐77)</a> - Library for calculating great circle distance.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/15/"/>
    <summary>2 awesome projects updated on Apr 13 - Apr 19, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/12/</id>
    <title>Awesome Machine Learning Updates on Mar 23 - Mar 29, 2015</title>
    <updated>2015-03-18T17:27:49.000Z</updated>
    <published>2015-03-17T05:31:59.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/oryxproject/oryx" rel="noopener noreferrer">ORYX (⭐1.8k)</a> - Lambda Architecture Framework using Apache Spark and Apache Kafka with a specialization for real-time large-scale machine learning.</li>
</ul>
<h3><p>.NET / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://accord-framework.net/" rel="noopener noreferrer">Accord-Framework</a> -The Accord.NET Framework is a complete framework for building machine learning, computer vision, computer audition, signal processing and statistical applications.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/12/"/>
    <summary>2 awesome projects updated on Mar 23 - Mar 29, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2015/7/</id>
    <title>Awesome Machine Learning Updates on Feb 16 - Feb 22, 2015</title>
    <updated>2015-02-10T04:30:13.000Z</updated>
    <published>2015-02-10T04:30:13.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/dmcc/PyStanfordDependencies" rel="noopener noreferrer">PyStanfordDependencies (⭐69)</a> - Python interface for converting Penn Treebank trees to Stanford Dependencies.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2015/7/"/>
    <summary>1 awesome projects updated on Feb 16 - Feb 22, 2015</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2014/50/</id>
    <title>Awesome Machine Learning Updates on Dec 15 - Dec 21, 2014</title>
    <updated>2014-12-08T17:39:56.000Z</updated>
    <published>2014-12-08T17:39:56.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/deap/deap" rel="noopener noreferrer">deap (⭐6.4k)</a> - Evolutionary algorithm framework.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2014/50/"/>
    <summary>1 awesome projects updated on Dec 15 - Dec 21, 2014</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2014/49/</id>
    <title>Awesome Machine Learning Updates on Dec 08 - Dec 14, 2014</title>
    <updated>2014-12-07T07:09:25.000Z</updated>
    <published>2014-12-07T07:09:25.000Z</published>
    <content type="html"><![CDATA[<h3><p>R / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/johnmyleswhite/ML_for_Hackers" rel="noopener noreferrer">Machine Learning For Hackers (⭐3.8k)</a></li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2014/49/"/>
    <summary>1 awesome projects updated on Dec 08 - Dec 14, 2014</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2014/48/</id>
    <title>Awesome Machine Learning Updates on Dec 01 - Dec 07, 2014</title>
    <updated>2014-11-30T19:20:36.000Z</updated>
    <published>2014-11-27T10:31:16.000Z</published>
    <content type="html"><![CDATA[<h3><p>.NET / Computer Vision</p>
</h3>
<ul>
<li><a href="http://www.aforgenet.com/framework/" rel="noopener noreferrer">AForge.NET</a> - Open source C# framework for developers and researchers in the fields of Computer Vision and Artificial Intelligence. Development has now shifted to GitHub.</li>
</ul>

<ul>
<li><a href="http://accord-framework.net" rel="noopener noreferrer">Accord.NET</a> - Together with AForge.NET, this library can provide image processing and computer vision algorithms to Windows, Windows RT and Windows Phone. Some components are also available for Java and Android.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/proycon/python-frog" rel="noopener noreferrer">python-frog (⭐49)</a> - Python binding to Frog, an NLP suite for Dutch. (pos tagging, lemmatisation, dependency parsing, NER)</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/proycon/python-timbl" rel="noopener noreferrer">python-timbl (⭐18)</a> - A Python extension module wrapping the full TiMBL C++ programming interface. Timbl is an elaborate k-Nearest Neighbours machine learning toolkit.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2014/48/"/>
    <summary>4 awesome projects updated on Dec 01 - Dec 07, 2014</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2014/34/</id>
    <title>Awesome Machine Learning Updates on Aug 25 - Aug 31, 2014</title>
    <updated>2014-08-20T17:42:43.000Z</updated>
    <published>2014-08-20T17:42:43.000Z</published>
    <content type="html"><![CDATA[<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/pyqtgraph/pyqtgraph" rel="noopener noreferrer">PyQtGraph (⭐4.3k)</a> - A pure-python graphics and GUI library built on PyQt4 / PySide and NumPy.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2014/34/"/>
    <summary>1 awesome projects updated on Aug 25 - Aug 31, 2014</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2014/31/</id>
    <title>Awesome Machine Learning Updates on Aug 04 - Aug 10, 2014</title>
    <updated>2014-08-02T01:09:35.000Z</updated>
    <published>2014-08-02T01:09:35.000Z</published>
    <content type="html"><![CDATA[<h3><p>Clojure / Data Analysis</p>
</h3>
<ul>
<li><a href="https://github.com/Netflix/PigPen" rel="noopener noreferrer">PigPen (⭐565)</a> - Map-Reduce for Clojure.</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/AirSage/Petrel" rel="noopener noreferrer">Petrel (⭐247)</a> - Tools for writing, submitting, debugging, and monitoring Storm topologies in pure Python.</li>
</ul>

<ul>
<li><a href="https://github.com/dfm/emcee" rel="noopener noreferrer">emcee (⭐1.6k)</a> - The Python ensemble sampling toolkit for affine-invariant MCMC.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/AllenDowney/DataScience" rel="noopener noreferrer">Allen Downey’s Data Science Course (⭐44)</a> - Code for Data Science at Olin College, Spring 2014.</li>
</ul>

<ul>
<li><a href="https://github.com/AllenDowney/ThinkBayes" rel="noopener noreferrer">Allen Downey’s Think Bayes Code (⭐1.7k)</a> - Code repository for Think Bayes.</li>
</ul>

<ul>
<li><a href="https://github.com/AllenDowney/ThinkComplexity" rel="noopener noreferrer">Allen Downey’s Think Complexity Code (⭐118)</a> - Code for Allen Downey's book Think Complexity.</li>
</ul>

<ul>
<li><a href="https://github.com/AllenDowney/ThinkOS" rel="noopener noreferrer">Allen Downey’s Think OS Code (⭐570)</a> - Text and supporting code for Think OS: A Brief Introduction to Operating Systems.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2014/31/"/>
    <summary>7 awesome projects updated on Aug 04 - Aug 10, 2014</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2014/30/</id>
    <title>Awesome Machine Learning Updates on Jul 28 - Aug 03, 2014</title>
    <updated>2014-07-27T15:14:57.000Z</updated>
    <published>2014-07-23T05:42:52.000Z</published>
    <content type="html"><![CDATA[<h3><p>Java / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://meka.sourceforge.net/" rel="noopener noreferrer">Meka</a> - An open source implementation of methods for multi-label classification and evaluation (extension to Weka).</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/fxsjy/jieba#jieba-1" rel="noopener noreferrer">jieba (⭐35k)</a> - Chinese Words Segmentation Utilities.</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/mattjj/pyhsmm" rel="noopener noreferrer">pyhsmm (⭐576)</a> - library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and explicit-duration Hidden semi-Markov Models (HSMMs), focusing on the Bayesian Nonparametric extensions, the HDP-HMM and HDP-HSMM, mostly with weak-limit approximations.</li>
</ul>

<ul>
<li><a href="https://github.com/EducationalTestingService/skll" rel="noopener noreferrer">SKLL (⭐561)</a> - A wrapper around scikit-learn that makes it simpler to conduct experiments.</li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2014/30/"/>
    <summary>4 awesome projects updated on Jul 28 - Aug 03, 2014</summary>
  </entry>
  <entry>
    <id>https://www.trackawesomelist.com/2014/29/</id>
    <title>Awesome Machine Learning Updates on Jul 21 - Jul 27, 2014</title>
    <updated>2014-07-19T00:52:13.000Z</updated>
    <published>2014-07-15T19:15:23.000Z</published>
    <content type="html"><![CDATA[<h3><p>C++ / Computer Vision</p>
</h3>
<ul>
<li><a href="http://dlib.net/imaging.html" rel="noopener noreferrer">DLib</a> - DLib has C++ and Python interfaces for face detection and training general object detectors.</li>
</ul>
<h3><p>Clojure / Data Analysis</p>
</h3>
<ul>
<li><a href="http://incanter.org/" rel="noopener noreferrer">Incanter</a> - Incanter is a Clojure-based, R-like platform for statistical computing and graphics.</li>
</ul>
<h3><p>Java / Natural Language Processing</p>
</h3>
<ul>
<li><a href="http://mallet.cs.umass.edu/" rel="noopener noreferrer">MALLET</a> - A Java-based package for statistical natural language processing, document classification, clustering, topic modelling, information extraction, and other machine learning applications to text.</li>
</ul>

<ul>
<li><a href="https://opennlp.apache.org/" rel="noopener noreferrer">OpenNLP</a> - A machine learning based toolkit for the processing of natural language text.</li>
</ul>

<ul>
<li><a href="http://alias-i.com/lingpipe/index.html" rel="noopener noreferrer">LingPipe</a> - A tool kit for processing text using computational linguistics.</li>
</ul>
<h3><p>Java / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/apache/spark" rel="noopener noreferrer">Spark (⭐43k)</a> - Spark is a fast and general engine for large-scale data processing.</li>
</ul>
<h3><p>JavaScript / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="http://nvd3.org/" rel="noopener noreferrer">NVD3.js</a></li>
</ul>

<ul>
<li><a href="http://dimplejs.org/" rel="noopener noreferrer">dimple</a></li>
</ul>
<h3><p>Julia / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/JuliaStats/PGM.jl" rel="noopener noreferrer">PGM (⭐53)</a> - A Julia framework for probabilistic graphical models.</li>
</ul>

<ul>
<li><a href="https://github.com/JuliaStats/Clustering.jl" rel="noopener noreferrer">Clustering (⭐373)</a> - Basic functions for clustering data: k-means, dp-means, etc.</li>
</ul>
<h3><p>Julia / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/JuliaStats/Distributions.jl" rel="noopener noreferrer">Distributions (⭐1.2k)</a> - A Julia package for probability distributions and associated functions.</li>
</ul>
<h3><p>Julia / Misc Stuff / Presentations</p>
</h3>
<ul>
<li><a href="https://github.com/JuliaDSP/DSP.jl" rel="noopener noreferrer">DSP (⭐416)</a> - Digital Signal Processing (filtering, periodograms, spectrograms, window functions).</li>
</ul>
<h3><p>Lua / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://numlua.luaforge.net/" rel="noopener noreferrer">Numeric Lua</a></li>
</ul>
<h3><p>Lua / Demos and Scripts</p>
</h3>
<ul>
<li><a href="https://github.com/e-lab/torch7-demos" rel="noopener noreferrer">Core torch7 demos repository (⭐43)</a>.<ul>
<li>linear-regression, logistic-regression</li>
<li>face detector (training and detection as separate demos)</li>
<li>mst-based-segmenter</li>
<li>train-a-digit-classifier</li>
<li>train-autoencoder</li>
<li>optical flow demo</li>
<li>train-on-housenumbers</li>
<li>train-on-cifar</li>
<li>tracking with deep nets</li>
<li>kinect demo</li>
<li>filter-bank visualization</li>
<li>saliency-networks</li>
</ul>
</li>
</ul>

<ul>
<li><a href="https://github.com/soumith/galaxyzoo" rel="noopener noreferrer">Training a Convnet for the Galaxy-Zoo Kaggle challenge(CUDA demo) (⭐35)</a></li>
</ul>

<ul>
<li><a href="https://github.com/rosejn/torch-datasets" rel="noopener noreferrer">torch-datasets (⭐36)</a> - Scripts to load several popular datasets including:<ul>
<li>BSR 500</li>
<li>CIFAR-10</li>
<li>COIL</li>
<li>Street View House Numbers</li>
<li>MNIST</li>
<li>NORB</li>
</ul>
</li>
</ul>
<h3><p>Matlab / Computer Vision</p>
</h3>
<ul>
<li><a href="http://www.ifp.illinois.edu/~minhdo/software/contourlet_toolbox.tar" rel="noopener noreferrer">Contourlets</a> - MATLAB source code that implements the contourlet transform and its utility functions.</li>
</ul>

<ul>
<li><a href="http://www.curvelet.org/software.html" rel="noopener noreferrer">Curvelets</a> - The Curvelet transform is a higher dimensional generalization of the Wavelet transform designed to represent images at different scales and different angles.</li>
</ul>
<h3><p>.NET / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/sergey-tihon/Stanford.NLP.NET/" rel="noopener noreferrer">Stanford.NLP for .NET (⭐611)</a> - A full port of Stanford NLP packages to .NET and also available precompiled as a NuGet package.</li>
</ul>
<h3><p>Python / Computer Vision</p>
</h3>
<ul>
<li><a href="http://simplecv.org/" rel="noopener noreferrer">SimpleCV</a> - An open source computer vision framework that gives access to several high-powered computer vision libraries, such as OpenCV. Written on Python and runs on Mac, Windows, and Ubuntu Linux.</li>
</ul>
<h3><p>Python / Natural Language Processing</p>
</h3>
<ul>
<li><a href="https://github.com/isnowfy/snownlp" rel="noopener noreferrer">SnowNLP (⭐6.6k)</a> - A library for processing Chinese text.</li>
</ul>

<ul>
<li><a href="https://github.com/columbia-applied-data-science/rosetta" rel="noopener noreferrer">Rosetta (⭐207)</a> - Text processing tools and wrappers (e.g. Vowpal Wabbit)</li>
</ul>
<h3><p>Python / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="http://spark.apache.org/docs/latest/mllib-guide.html" rel="noopener noreferrer">MLlib in Apache Spark</a> - Distributed machine learning library in Spark</li>
</ul>

<ul>
<li><a href="https://bigml.com" rel="noopener noreferrer">BigML</a> - A library that contacts external servers.</li>
</ul>

<ul>
<li><a href="https://github.com/clips/pattern" rel="noopener noreferrer">pattern (⭐8.9k)</a> - Web mining module for Python.</li>
</ul>

<ul>
<li><a href="https://github.com/numenta/nupic" rel="noopener noreferrer">NuPIC (⭐6.4k)</a> - Numenta Platform for Intelligent Computing.</li>
</ul>

<ul>
<li><a href="https://github.com/pybrain/pybrain" rel="noopener noreferrer">PyBrain (⭐2.9k)</a> - Another Python Machine Learning Library.</li>
</ul>

<ul>
<li><a href="https://github.com/ocelma/python-recsys" rel="noopener noreferrer">python-recsys (⭐1.5k)</a> - A Python library for implementing a Recommender System.</li>
</ul>

<ul>
<li><a href="https://github.com/echen/restricted-boltzmann-machines" rel="noopener noreferrer">Restricted Boltzmann Machines (⭐970)</a> -Restricted Boltzmann Machines in Python. [DEEP LEARNING]</li>
</ul>
<h3><p>Python / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://networkx.github.io/" rel="noopener noreferrer">NetworkX</a> - A high-productivity software for complex networks.</li>
</ul>

<ul>
<li><a href="https://github.com/pymc-devs/pymc" rel="noopener noreferrer">PyMC (⭐9.6k)</a> - Markov Chain Monte Carlo sampling toolkit.</li>
</ul>

<ul>
<li><a href="https://github.com/quantopian/zipline" rel="noopener noreferrer">zipline (⭐20k)</a> - A Pythonic algorithmic trading library.</li>
</ul>

<ul>
<li><a href="https://github.com/sympy/sympy" rel="noopener noreferrer">SymPy (⭐15k)</a> - A Python library for symbolic mathematics.</li>
</ul>

<ul>
<li><a href="https://github.com/statsmodels/statsmodels" rel="noopener noreferrer">statsmodels (⭐11k)</a> - Statistical modelling and econometrics in Python.</li>
</ul>

<ul>
<li><a href="https://github.com/kartograph/kartograph.py" rel="noopener noreferrer">Kartograph.py (⭐999)</a> - Rendering beautiful SVG maps in Python.</li>
</ul>
<h3><p>Python / Misc Scripts / iPython Notebooks / Codebases</p>
</h3>
<ul>
<li><a href="https://github.com/rasbt/pattern_classification" rel="noopener noreferrer">pattern_classification (⭐4.2k)</a></li>
</ul>

<ul>
<li><a href="https://github.com/Wavelets/ThinkStats2" rel="noopener noreferrer">thinking stats 2 (⭐8)</a></li>
</ul>

<ul>
<li><a href="https://github.com/hyperopt/hyperopt-sklearn" rel="noopener noreferrer">hyperopt (⭐1.6k)</a></li>
</ul>

<ul>
<li><a href="https://github.com/numenta/nupic" rel="noopener noreferrer">numpic (⭐6.4k)</a></li>
</ul>

<ul>
<li><a href="https://github.com/ogrisel/notebooks" rel="noopener noreferrer">ipython-notebooks (⭐575)</a></li>
</ul>

<ul>
<li><a href="https://github.com/CamDavidsonPilon/decision-weights" rel="noopener noreferrer">decision-weights (⭐33)</a></li>
</ul>

<ul>
<li><a href="https://github.com/Wavelets/sarah-palin-lda" rel="noopener noreferrer">Sarah Palin LDA (⭐9)</a> - Topic Modelling the Sarah Palin emails.</li>
</ul>

<ul>
<li><a href="https://github.com/madhusudancs/sentiment-analyzer" rel="noopener noreferrer">sentiment-analyzer (⭐51)</a> - Tweets Sentiment Analyzer</li>
</ul>

<ul>
<li><a href="https://github.com/kevincobain2000/sentiment_classifier" rel="noopener noreferrer">sentiment_classifier (⭐170)</a> - Sentiment classifier using word sense disambiguation.</li>
</ul>

<ul>
<li><a href="https://github.com/kevincobain2000/jProcessing" rel="noopener noreferrer">jProcessing (⭐147)</a> - Kanji / Hiragana / Katakana to Romaji Converter. Edict Dictionary &amp; parallel sentences Search. Sentence Similarity between two JP Sentences. Sentiment Analysis of Japanese Text. Run Cabocha(ISO--8859-1 configured) in Python.</li>
</ul>
<h3><p>Python / Kaggle Competition Source Code</p>
</h3>
<ul>
<li><a href="https://github.com/zygmuntz/kaggle-bestbuy_small" rel="noopener noreferrer">kaggle-bestbuy_small (⭐6)</a></li>
</ul>
<h3><p>Ruby / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/cardmagic/classifier" rel="noopener noreferrer">CardMagic-Classifier (⭐719)</a> - A general classifier module to allow Bayesian and other types of classifications.</li>
</ul>
<h3><p>Ruby / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="http://sciruby.com/" rel="noopener noreferrer">SciRuby</a></li>
</ul>

<ul>
<li><a href="https://github.com/bioruby/bioruby" rel="noopener noreferrer">Bioruby (⭐381)</a></li>
</ul>
<h3><p>Ruby / Misc</p>
</h3>
<ul>
<li><a href="https://github.com/infochimps-labs/big_data_for_chimps" rel="noopener noreferrer">Big Data For Chimps (⭐169)</a></li>
</ul>
<h3><p>Scala / Natural Language Processing</p>
</h3>
<ul>
<li><a href="http://www.scalanlp.org/" rel="noopener noreferrer">ScalaNLP</a> - ScalaNLP is a suite of machine learning and numerical computing libraries.</li>
</ul>

<ul>
<li><a href="https://github.com/scalanlp/breeze" rel="noopener noreferrer">Breeze (⭐3.5k)</a> - Breeze is a numerical processing library for Scala.</li>
</ul>

<ul>
<li><a href="https://github.com/factorie/factorie" rel="noopener noreferrer">FACTORIE (⭐554)</a> - FACTORIE is a toolkit for deployable probabilistic modelling, implemented as a software library in Scala. It provides its users with a succinct language for creating relational factor graphs, estimating parameters and performing inference.</li>
</ul>
<h3><p>Scala / Data Analysis / Data Visualization</p>
</h3>
<ul>
<li><a href="https://github.com/BIDData/BIDMat" rel="noopener noreferrer">BIDMat (⭐269)</a> - CPU and GPU-accelerated matrix library intended to support large-scale exploratory data analysis.</li>
</ul>
<h3><p>Scala / General-Purpose Machine Learning</p>
</h3>
<ul>
<li><a href="https://github.com/bigdatagenomics/adam" rel="noopener noreferrer">adam (⭐1k)</a> - A genomics processing engine and specialized file format built using Apache Avro, Apache Spark and Parquet. Apache 2 licensed.</li>
</ul>

<ul>
<li><a href="https://github.com/bioscala/bioscala" rel="noopener noreferrer">bioscala (⭐115)</a> - Bioinformatics for the Scala programming language</li>
</ul>

<ul>
<li><a href="https://github.com/BIDData/BIDMach" rel="noopener noreferrer">BIDMach (⭐919)</a> - CPU and GPU-accelerated Machine Learning Library.</li>
</ul>

<ul>
<li><a href="https://github.com/p2t2/figaro" rel="noopener noreferrer">Figaro (⭐758)</a> - a Scala library for constructing probabilistic models.</li>
</ul>
<h3><p>Credits / Misc</p>
</h3>
<ul>
<li>Some of the python libraries were cut-and-pasted from <a href="https://github.com/vinta/awesome-python" rel="noopener noreferrer">vinta (⭐294k)</a></li>
</ul>
]]></content>
    <link rel="alternate" href="https://www.trackawesomelist.com/2014/29/"/>
    <summary>59 awesome projects updated on Jul 21 - Jul 27, 2014</summary>
  </entry>
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