Awesome List Updates on Aug 31, 2019
4 awesome lists updated today.
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1. Awesome Machine Learning
Go / General-Purpose Machine Learning
- go-dnn (⭐5) - Deep Neural Networks for Golang (powered by MXNet)
2. Awesome Aws
Open Source Repos / Glacier
- vsespb/mt-aws-glacier 🔥🔥🔥 (⭐535) - Perl Multithreaded Multipart sync to Glacier.
3. Awesome Ruby
Database Tools
- Rein (⭐670) - Database constraints made easy for ActiveRecord.
4. Awesome Python Data Science
Machine Learning / General Purpose Machine Learning
- scikit-learn - Machine learning in Python.
- cuML (⭐3.6k) - RAPIDS Machine Learning Library.
- modAL (⭐2k) - Modular active learning framework for Python3.
- Sparkit-learn (⭐1.1k) - PySpark + scikit-learn = Sparkit-learn.
- MLxtend (⭐4.5k) - Extension and helper modules for Python's data analysis and machine learning libraries.
- Reproducible Experiment Platform (REP) (⭐676) - Machine Learning toolbox for Humans.
- scikit-multilearn (⭐871) - Multi-label classification for python.
- seqlearn (⭐666) - Sequence classification toolkit for Python.
- pystruct (⭐664) - Simple structured learning framework for Python.
- RuleFit (⭐388) - Implementation of the rulefit.
- metric-learn (⭐1.3k) - Metric learning algorithms in Python.
Machine Learning / Gradient Boosting
- XGBoost (⭐25k) - Scalable, Portable, and Distributed Gradient Boosting.
- LightGBM (⭐16k) - A fast, distributed, high-performance gradient boosting.
- CatBoost (⭐7.4k) - An open-source gradient boosting on decision trees library.
- ThunderGBM (⭐675) - Fast GBDTs and Random Forests on GPUs.
Machine Learning / Ensemble Methods
- ML-Ensemble - High performance ensemble learning.
- Stacking (⭐204) - Simple and useful stacking library written in Python.
- stacked_generalization (⭐116) - Library for machine learning stacking generalization.
- vecstack (⭐677) - Python package for stacking (machine learning technique).
Machine Learning / Imbalanced Datasets
- imbalanced-learn (⭐6.5k) - Module to perform under-sampling and over-sampling with various techniques.
- imbalanced-algorithms (⭐226) - Python-based implementations of algorithms for learning on imbalanced data.
Machine Learning / Random Forests
- rpforest (⭐221) - A forest of random projection trees.
- sklearn-random-bits-forest (⭐9) - Wrapper of the Random Bits Forest program written by (Wang et al., 2016).
- rgf_python (⭐366) - Python Wrapper of Regularized Greedy Forest.
Machine Learning / Kernel Methods
- pyFM (⭐916) - Factorization machines in python.
- fastFM (⭐1.1k) - A library for Factorization Machines.
- tffm (⭐785) - TensorFlow implementation of an arbitrary order Factorization Machine.
- scikit-rvm (⭐219) - Relevance Vector Machine implementation using the scikit-learn API.
- ThunderSVM (⭐1.5k) - A fast SVM Library on GPUs and CPUs.
Deep Learning / PyTorch
- PyTorch (⭐72k) - Tensors and Dynamic neural networks in Python with strong GPU acceleration.
- ignite (⭐4.4k) - High-level library to help with training neural networks in PyTorch.
- skorch (⭐5.4k) - A scikit-learn compatible neural network library that wraps PyTorch.
Deep Learning / TensorFlow
- TensorFlow (⭐178k) - Computation using data flow graphs for scalable machine learning by Google.
- TensorLayer (⭐7.2k) - Deep Learning and Reinforcement Learning Library for Researcher and Engineer.
- TFLearn (⭐9.6k) - Deep learning library featuring a higher-level API for TensorFlow.
- Sonnet (⭐9.6k) - TensorFlow-based neural network library.
- Polyaxon (⭐3.4k) - A platform that helps you build, manage and monitor deep learning models.
- tfdeploy (⭐352) - Deploy TensorFlow graphs for fast evaluation and export to TensorFlow-less environments running numpy.
- tensorflow-upstream (⭐661) - TensorFlow ROCm port.
- TensorFlow Fold (⭐1.8k) - Deep learning with dynamic computation graphs in TensorFlow.
- TensorLight (⭐10) - A high-level framework for TensorFlow.
- Mesh TensorFlow (⭐1.5k) - Model Parallelism Made Easier.
- Ludwig (⭐9.9k) - A toolbox that allows one to train and test deep learning models without the need to write code.
Deep Learning / MXNet
- MXNet (⭐21k) - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler.
- Gluon (⭐2.3k) - A clear, concise, simple yet powerful and efficient API for deep learning (now included in MXNet).
- Xfer (⭐251) - Transfer Learning library for Deep Neural Networks.
- MXNet (⭐29) - HIP Port of MXNet.
Automated Machine Learning / Others
- auto-sklearn (⭐7.2k) - An AutoML toolkit and a drop-in replacement for a scikit-learn estimator.
- TPOT (⭐9.3k) - AutoML tool that optimizes machine learning pipelines using genetic programming.
Natural Language Processing / Others
- torchtext (⭐3.4k) - Data loaders and abstractions for text and NLP.
- gluon-nlp (⭐2.5k) - NLP made easy.
- pyMorfologik (⭐18) - Python binding for Morfologik.
- skift (⭐233) - Scikit-learn wrappers for Python fastText.
- flair (⭐13k) - Very simple framework for state-of-the-art NLP.
Computer Audition / Others
- torchaudio (⭐2.2k) - An audio library for PyTorch.
Computer Vision / Others
- torchvision (⭐15k) - Datasets, Transforms, and Models specific to Computer Vision.
- gluon-cv (⭐5.6k) - Provides implementations of the state-of-the-art deep learning models in computer vision.
Graph Machine Learning / Others
- pytorch_geometric (⭐19k) - Geometric Deep Learning Extension Library for PyTorch.
Probabilistic Methods / Others
- pyro (⭐8.2k) - A flexible, scalable deep probabilistic programming library built on PyTorch.
- ZhuSuan - Bayesian Deep Learning.
- GPflow - Gaussian processes in TensorFlow.
- InferPy (⭐144) - Deep Probabilistic Modelling Made Easy.
- sklearn-bayes (⭐494) - Python package for Bayesian Machine Learning with scikit-learn API.
- skpro (⭐123) - Supervised domain-agnostic prediction framework for probabilistic modelling by The Alan Turing Institute.
- PyVarInf (⭐349) - Bayesian Deep Learning methods with Variational Inference for PyTorch.
- GPyTorch (⭐3.2k) - A highly efficient and modular implementation of Gaussian Processes in PyTorch.
- sklearn-crfsuite (⭐421) - A scikit-learn-inspired API for CRFsuite.
Model Explanation / Others
- Contrastive Explanation (⭐43) - Contrastive Explanation (Foil Trees).
- yellowbrick (⭐4.1k) - Visual analysis and diagnostic tools to facilitate machine learning model selection.
- scikit-plot (⭐2.4k) - An intuitive library to add plotting functionality to scikit-learn objects.
- shap (⭐20k) - A unified approach to explain the output of any machine learning model.
- Lime (⭐11k) - Explaining the predictions of any machine learning classifier.
- FairML (⭐353) - FairML is a python toolbox auditing the machine learning models for bias.
- model-analysis (⭐1.2k) - Model analysis tools for TensorFlow.
- themis-ml (⭐118) - A library that implements fairness-aware machine learning algorithms.
- treeinterpreter (⭐729) - Interpreting scikit-learn's decision tree and random forest predictions.
- mxboard (⭐325) - Logging MXNet data for visualization in TensorBoard.
Genetic Programming / Others
- gplearn (⭐1.4k) - Genetic Programming in Python.
- karoo_gp (⭐152) - A Genetic Programming platform for Python with GPU support.
- sklearn-genetic (⭐282) - Genetic feature selection module for scikit-learn.
Optimization / Others
- BoTorch (⭐2.8k) - Bayesian optimization in PyTorch.
- hyperopt-sklearn (⭐1.5k) - Hyper-parameter optimization for sklearn.
- sklearn-deap (⭐739) - Use evolutionary algorithms instead of gridsearch in scikit-learn.
- sigopt_sklearn (⭐74) - SigOpt wrappers for scikit-learn methods.
- GPflowOpt (⭐260) - Bayesian Optimization using GPflow.
Feature Engineering / General
- skl-groups (⭐41) - A scikit-learn addon to operate on set/"group"-based features.
- Feature Forge (⭐382) - A set of tools for creating and testing machine learning features.
- few (⭐47) - A feature engineering wrapper for sklearn.
- scikit-mdr (⭐123) - A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
- tsfresh (⭐7.8k) - Automatic extraction of relevant features from time series.
Feature Engineering / Feature Selection
- scikit-feature (⭐1.4k) - Feature selection repository in Python.
- boruta_py (⭐1.4k) - Implementations of the Boruta all-relevant feature selection method.
- BoostARoota (⭐201) - A fast xgboost feature selection algorithm.
- scikit-rebate (⭐385) - A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
Statistics / NLP
- pandas_summary (⭐486) - Extension to pandas dataframes describe function.
- Pandas Profiling (⭐11k) - Create HTML profiling reports from pandas DataFrame objects.
- Alphalens (⭐2.9k) - Performance analysis of predictive (alpha) stock factors.
Data Manipulation / Data Frames
- datatable (⭐1.8k) - Data.table for Python.
- cuDF (⭐6k) - GPU DataFrame Library.
- blaze (⭐3.2k) - NumPy and pandas interface to Big Data.
- pandasql (⭐1.3k) - Allows you to query pandas DataFrames using SQL syntax.
- pandas-gbq (⭐389) - pandas Google Big Query.
- pysparkling (⭐260) - A pure Python implementation of Apache Spark's RDD and DStream interfaces.
- modin (⭐9k) - Speed up your pandas workflows by changing a single line of code.
Data Manipulation / Pipelines
- pandas-ply (⭐196) - Functional data manipulation for pandas.
- Dplython (⭐759) - Dplyr for Python.
- sklearn-pandas (⭐2.8k) - pandas integration with sklearn.
- pyjanitor (⭐1.2k) - Clean APIs for data cleaning.
Experimentation / Synthetic Data
- Sacred (⭐4.1k) - A tool to help you configure, organize, log, and reproduce experiments.
- Ax (⭐2.2k) - Adaptive Experimentation Platform.
Computations / Synthetic Data
- Dask (⭐11k) - Parallel computing with task scheduling.
Spatial Analysis / Synthetic Data
- GeoPandas (⭐3.9k) - Python tools for geographic data.
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