Awesome List Updates on Feb 23, 2017

9 awesome lists updated today.

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1. Awesome Bigdata

Distributed Programming

• Rackerlabs Blueflood - multi-tenant distributed metric processing system

Key Map Data Model

• ScyllaDB - column-oriented distributed datastore written in C++, totally compatible with Apache Cassandra.

Graph Data Model

• GraphLab PowerGraph - a core C++ GraphLab API and a collection of high-performance machine learning and data mining toolkits built on top of the GraphLab API.

Benchmarking

• Yahoo Gridmix3 - Hadoop cluster benchmarking from Yahoo engineer team.

Data Visualization

• Lumify - open source big data analysis and visualization platform

2. Awesome Research

More / HTML+CSS+JS

• DiRT Directory: Registry of digital research tools for scholarly use.

3. Awesome Flexbox

Tools / Slides and Notes

• Try Flexbox

4. Tips

Show git status short

git status --short --branch

5. Awesome Dev Fun

Ruby

• Nyan Cat RSpec Formatter (⭐738) - Nyan Cat inspired RSpec formatter!

6. Awesome Tensorflow

Tutorials

• Getting Started with TensorFlow on Android - Build your first TensorFlow Android app

7. Awesome Deep Learning Papers

Awesome list criteria

• Papers that are important, but failed to be included in the list, will be listed in More than Top 100 section.

• 2015 : +200 citations

• 2014 : +400 citations

• 2013 : +600 citations

• Can anyone contribute the code for obtaining the statistics of the authors of Top-100 papers?

Contents / Understanding / Generalization / Transfer

• CNN features off-the-Shelf: An astounding baseline for recognition (2014), A. Razavian et al. [pdf]

• Visualizing and understanding convolutional networks (2014), M. Zeiler and R. Fergus [pdf]

• Decaf: A deep convolutional activation feature for generic visual recognition (2014), J. Donahue et al. [pdf]

Contents / Optimization / Training Techniques

• Delving deep into rectifiers: Surpassing human-level performance on imagenet classification (2015), K. He et al. [pdf]

• Dropout: A simple way to prevent neural networks from overfitting (2014), N. Srivastava et al. [pdf]

Contents / Unsupervised / Generative Models

• Building high-level features using large scale unsupervised learning (2013), Q. Le et al. [pdf]

Contents / Convolutional Neural Network Models

• Deep residual learning for image recognition (2016), K. He et al. [pdf]

• Going deeper with convolutions (2015), C. Szegedy et al. [pdf]

• Very deep convolutional networks for large-scale image recognition (2014), K. Simonyan and A. Zisserman [pdf]

• Return of the devil in the details: delving deep into convolutional nets (2014), K. Chatfield et al. [pdf]

• ImageNet classification with deep convolutional neural networks (2012), A. Krizhevsky et al. [pdf]

Contents / Image: Segmentation / Object Detection

• Fully convolutional networks for semantic segmentation (2015), J. Long et al. [pdf]

• Rich feature hierarchies for accurate object detection and semantic segmentation (2014), R. Girshick et al. [pdf]

Contents / Image / Video / Etc

• Deep visual-semantic alignments for generating image descriptions (2015), A. Karpathy and L. Fei-Fei [pdf]

• Show, attend and tell: Neural image caption generation with visual attention (2015), K. Xu et al. [pdf]

• Long-term recurrent convolutional networks for visual recognition and description (2015), J. Donahue et al. [pdf]

• Large-scale video classification with convolutional neural networks (2014), A. Karpathy et al. [pdf]

Contents / Natural Language Processing / RNNs

• Neural machine translation by jointly learning to align and translate (2014), D. Bahdanau et al. [pdf]

• Sequence to sequence learning with neural networks (2014), I. Sutskever et al. [pdf]

• A convolutional neural network for modeling sentences (2014), N. Kalchbrenner et al. [pdf]

• Glove: Global vectors for word representation (2014), J. Pennington et al. [pdf]

• Distributed representations of sentences and documents (2014), Q. Le and T. Mikolov [pdf]

• Efficient estimation of word representations in vector space (2013), T. Mikolov et al. [pdf]

• Recursive deep models for semantic compositionality over a sentiment treebank (2013), R. Socher et al. [pdf]

Contents / Speech / Other Domain

• Deep speech 2: End-to-end speech recognition in English and Mandarin (2015), D. Amodei et al. [pdf]

• Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups (2012), G. Hinton et al. [pdf]

• Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition (2012) G. Dahl et al. [pdf]

Contents / Reinforcement Learning / Robotics

• End-to-end training of deep visuomotor policies (2016), S. Levine et al. [pdf]

• Mastering the game of Go with deep neural networks and tree search (2016), D. Silver et al. [pdf]

• Human-level control through deep reinforcement learning (2015), V. Mnih et al. [pdf]

Contents / More Papers from 2016

• Colorful image colorization (2016), R. Zhang et al. [pdf]

• SSD: Single shot multibox detector (2016), W. Liu et al. [pdf]

Contents / Old Papers

• Natural language processing (almost) from scratch (2011), R. Collobert et al. [pdf]

Contents / HW / SW / Dataset

• TensorFlow: Large-scale machine learning on heterogeneous distributed systems (2016), M. Abadi et al. [pdf]

• Theano: A Python framework for fast computation of mathematical expressions, R. Al-Rfou et al.

• Caffe: Convolutional architecture for fast feature embedding (2014), Y. Jia et al. [pdf]

Contents / Book / Survey / Review

• Deep learning (2015), Y. LeCun, Y. Bengio and G. Hinton [pdf]

• Deep learning in neural networks: An overview (2015), J. Schmidhuber [pdf]

• Representation learning: A review and new perspectives (2013), Y. Bengio et al. [pdf]

Contents / Appendix: More than Top 100

• Beyond short snippents: Deep networks for video classification (2015) [pdf]

• Large scale distributed deep networks (2012), J. Dean et al. [pdf]

8. Awesome Android Ui

SeekBar

• Name: PreviewSeekBar (⭐3.3k)

  License: Apache License V2

  Demo:

Animation

• Name: Lottie for Android (⭐33k)

  License: Apache License V2

  Demo:

9. Awesome Dotnet

Interoperability

• pythonnet (⭐4.2k) - Python and .NET interop framework

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