A curated list of awesome TensorFlow experiments, libraries, and projects. Inspired by awesome-machine-learning.
TensorFlow is an open source software library for numerical computation using data flow graphs. In other words, the best way to build deep learning models.
More info here.
## Tutorials * [TensorFlow Tutorial 1](https://github.com/pkmital/tensorflow_tutorials) - From the basics to slightly more interesting applications of TensorFlow * [TensorFlow Tutorial 2](https://github.com/nlintz/TensorFlow-Tutorials) - Introduction to deep learning based on Google's TensorFlow framework. These tutorials are direct ports of Newmu's Theano * [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) - TensorFlow tutorials and code examples for beginners ## Models/Projects * [Pretty Tensor](https://github.com/google/prettytensor) - Pretty Tensor provides a high level builder API * [Neural Style](https://github.com/anishathalye/neural-style) - An implementation of neural style * [TensorFlow White Paper Notes](https://github.com/samjabrahams/tensorflow-white-paper-notes) - Annotated notes and summaries of the TensorFlow white paper, along with SVG figures and links to documentation * [NeuralArt](https://github.com/ckmarkoh/neuralart_tensorflow) - Implementation of A Neural Algorithm of Artistic Style * [Deep-Q learning Pong with TensorFlow and PyGame](http://www.danielslater.net/2016/03/deep-q-learning-pong-with-tensorflow.html) * [Generative Handwriting Demo using TensorFlow](https://github.com/hardmaru/write-rnn-tensorflow) - An attempt to implement the random handwriting generation portion of Alex Graves' paper * [Neural Turing Machine in TensorFlow](https://github.com/carpedm20/NTM-tensorflow) - implementation of Neural Turing Machine * [GoogleNet Convolutional Neural Network Groups Movie Scenes By Setting] (https://github.com/agermanidis/thingscoop) - Search, filter, and describe videos based on objects, places, and other things that appear in them * [Neural machine translation between the writings of Shakespeare and modern English using TensorFlow](https://github.com/tokestermw/tensorflow-shakespeare) - This performs a monolingual translation, going from modern English to Shakespeare and vis-versa. * [Colornet - Neural Network to colorize grayscale images] (https://github.com/pavelgonchar/colornet) - Neural Network to colorize grayscale images * [Neural Caption Generator](https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow) - Implementation of ["Show and Tell"](http://arxiv.org/abs/1411.4555) * [Neural Caption Generator with Attention](https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow) - Implementation of ["Show, Attend and Tell"](http://arxiv.org/abs/1502.03044) * [Weakly_detector](https://github.com/jazzsaxmafia/Weakly_detector) - Implementation of ["Learning Deep Features for Discriminative Localization"](http://cnnlocalization.csail.mit.edu/) * [Dynamic Capacity Networks](https://github.com/jazzsaxmafia/dcn.tf) - Implementation of ["Dynamic Capacity Networks"](http://arxiv.org/abs/1511.07838) * [HMM in TensorFlow](https://github.com/dwiel/tensorflow_hmm) - Implementation of viterbi and forward/backward algorithms for HMM ## Powered by TensorFlow * [YOLO TensorFlow](https://github.com/gliese581gg/YOLO_tensorflow) - Implementation of 'YOLO : Real-Time Object Detection' ## Libraries * [skflow](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/learn/python/learn) - Simplified interface (mimicking Scikit Learn) for Deep Learning (now part of TensorFlow as TF Learn Module) * [tflearn](https://github.com/tflearn/tflearn) - Deep learning library featuring a higher-level API * [TensorFlow-Slim](https://github.com/tensorflow/models/tree/master/inception/inception/slim) - High-level library for defining models * [caffe-tensorflow](https://github.com/ethereon/caffe-tensorflow) - Convert Caffe models to TensorFlow format * [keras](http://keras.io) - Minimal, modular deep learning library for TensorFlow and Theano ##Videos * [TensorFlow Guide 1](http://bit.ly/1OX8s8Y) - A guide to installation and use * [TensorFlow Guide 2](http://bit.ly/1R27Ki9) - Continuation of first video * [TensorFlow Basic Usage](http://bit.ly/1TCNmEY) - A guide going over basic usage * [TensorFlow Deep MNIST for Experts](http://bit.ly/1L9IfJx) - Goes over Deep MNIST * [TensorFlow Udacity Deep Learning](https://www.youtube.com/watch?v=ReaxoSIM5XQ) - Basic steps to install TensorFlow for free on the Cloud 9 online service with 1Gb of data * [Why Google wants everyone to have access to TensorFlow](http://video.foxnews.com/v/4611174773001/why-google-wants-everyone-to-have-access-to-tensorflow/?#sp=show-clips) * [Videos from TensorFlow Silicon Valley Meet Up 1/19/2016](http://blog.altoros.com/videos-from-tensorflow-silicon-valley-meetup-january-19-2016.html) * [Videos from TensorFlow Silicon Valley Meet Up 1/21/2016](http://blog.altoros.com/videos-from-tensorflow-seattle-meetup-jan-21-2016.html) ##Papers * [TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](http://download.tensorflow.org/paper/whitepaper2015.pdf) - This paper describes the TensorFlow interface and an implementation of that interface that we have built at Google * [Comparative Study of Deep Learning Software Frameworks](http://arxiv.org/abs/1511.06435) - The study is performed on several types of deep learning architectures and we evaluate the performance of the above frameworks when employed on a single machine for both (multi-threaded) CPU and GPU (Nvidia Titan X) settings * [Distributed TensorFlow with MPI](http://arxiv.org/abs/1603.02339) - In this paper, we extend recently proposed Google TensorFlow for execution on large scale clusters using Message Passing Interface (MPI) ##Blog posts * [TensorFlow: smarter machine learning, for everyone](https://googleblog.blogspot.com/2015/11/tensorflow-smarter-machine-learning-for.html) - An introduction to TensorFlow * [Why TensorFlow will change the Game for AI](http://www.somatic.io/blog/why-tensorflow-will-change-the-game-for-ai) * [TensorFlow for Poets](http://petewarden.com/2016/02/28/tensorflow-for-poets) - Goes over the implementation of TensorFlow * [Introduction to Scikit Flow - Simplified Interface to TensorFlow](http://terrytangyuan.github.io/2016/03/14/scikit-flow-intro/) - Key Features Illustrated * [The indico Machine Learning Team's take on TensorFlow](https://indico.io/blog/indico-tensorflow) ## Community * [Stack Overflow](http://stackoverflow.com/questions/tagged/tensorflow) * [@TensorFlo on Twitter](https://twitter.com/TensorFlo) * [Reddit](https://www.reddit.com/r/tensorflow) * [Mailing List](https://groups.google.com/a/tensorflow.org/forum/#!forum/discuss) ## Books * [First Contact with TensorFlow](http://www.jorditorres.org/first-contact-with-tensorflow/) ## Contributions Your contributions are always welcome!If you want to contribute to this list (please do), send me a pull request or contact me @jtoy Also, when you noticed that listed repository should be deprecated.
- Repository's owner explicitly say that "this library is not maintained".
- Not committed for long time (2~3 years).
More info on the guidelines
## Credits