[38;5;12m                                   [39m[38;2;255;187;0m[1m[4mAwesome TensorFlow  [0m[38;5;14m[1m[4m![0m[38;2;255;187;0m[1m[4mAwesome[0m[38;5;14m[1m[4m (https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)[0m[38;2;255;187;0m[1m[4m (https://github.com/jtoy/awesome)[0m

[38;5;12mA curated list of awesome TensorFlow experiments, libraries, and projects. Inspired by awesome-machine-learning.[39m

[38;2;255;187;0m[4mWhat is TensorFlow?[0m

[38;5;12mTensorFlow is an open source software library for numerical computation using data flow graphs. In other words, the best way to build deep learning models.[39m

[38;5;12mMore info [39m[38;5;14m[1mhere[0m[38;5;12m (http://tensorflow.org).[39m



[38;2;255;187;0m[4mTable of Contents[0m


[38;5;12m- [39m[38;5;14m[1mTutorials[0m[38;5;12m (#github-tutorials)[39m
[38;5;12m- [39m[38;5;14m[1mModels/Projects[0m[38;5;12m (#github-projects)[39m
[38;5;12m- [39m[38;5;14m[1mPowered by TensorFlow[0m[38;5;12m (#github-powered-by)[39m
[38;5;12m- [39m[38;5;14m[1mLibraries[0m[38;5;12m (#libraries)[39m
[38;5;12m- [39m[38;5;14m[1mTools/Utilities[0m[38;5;12m (#tools-utils)[39m
[38;5;12m- [39m[38;5;14m[1mVideos[0m[38;5;12m (#video)[39m
[38;5;12m- [39m[38;5;14m[1mPapers[0m[38;5;12m (#papers)[39m
[38;5;12m- [39m[38;5;14m[1mBlog posts[0m[38;5;12m (#blogs)[39m
[38;5;12m- [39m[38;5;14m[1mCommunity[0m[38;5;12m (#community)[39m
[38;5;12m- [39m[38;5;14m[1mBooks[0m[38;5;12m (#books)[39m






[38;2;255;187;0m[4mTutorials[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Tutorial 1[0m[38;5;12m (https://github.com/pkmital/tensorflow_tutorials) - From the basics to slightly more interesting applications of TensorFlow[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Tutorial 2[0m[38;5;12m (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[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Tutorial 3[0m[38;5;12m (https://github.com/Hvass-Labs/TensorFlow-Tutorials) - These tutorials are intended for beginners in Deep Learning and TensorFlow with well-documented code and YouTube videos.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Examples[0m[38;5;12m (https://github.com/aymericdamien/TensorFlow-Examples) - TensorFlow tutorials and code examples for beginners[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSungjoon's TensorFlow-101[0m[38;5;12m (https://github.com/sjchoi86/Tensorflow-101) - TensorFlow tutorials written in Python with Jupyter Notebook[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTerry Um’s TensorFlow Exercises[0m[38;5;12m (https://github.com/terryum/TensorFlow_Exercises) - Re-create the codes from other TensorFlow examples[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mInstalling TensorFlow on Raspberry Pi 3[0m[38;5;12m (https://github.com/samjabrahams/tensorflow-on-raspberry-pi) - TensorFlow compiled and running properly on the Raspberry Pi[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mClassification on time series[0m[38;5;12m (https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition) - Recurrent Neural Network classification in TensorFlow with LSTM on cellphone sensor data[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGetting Started with TensorFlow on Android[0m[38;5;12m (https://omid.al/posts/2017-02-20-Tutorial-Build-Your-First-Tensorflow-Android-App.html) - Build your first TensorFlow Android app[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mPredict time series[0m[38;5;12m (https://github.com/guillaume-chevalier/seq2seq-signal-prediction) - Learn to use a seq2seq model on simple datasets as an introduction to the vast array of possibilities that this architecture offers[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSingle Image Random Dot Stereograms[0m
[38;5;12m (https://github.com/Mazecreator/TensorFlow-SIRDS) - SIRDS is a means to present 3D data in a 2D image. It allows for scientific data display of a waterfall type plot with no hidden lines due to perspective.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCS20[0m[38;5;14m[1m [0m[38;5;14m[1mSI:[0m[38;5;14m[1m [0m[38;5;14m[1mTensorFlow[0m[38;5;14m[1m [0m[38;5;14m[1mfor[0m[38;5;14m[1m [0m[38;5;14m[1mDeepLearning[0m[38;5;14m[1m [0m[38;5;14m[1mResearch[0m[38;5;12m [39m[38;5;12m(http://web.stanford.edu/class/cs20si/syllabus.html)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mStanford[39m[38;5;12m [39m[38;5;12mCourse[39m[38;5;12m [39m[38;5;12mabout[39m[38;5;12m [39m[38;5;12mTensorflow[39m[38;5;12m [39m[38;5;12mfrom[39m[38;5;12m [39m[38;5;12m2017[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;14m[1mSyllabus[0m[38;5;12m [39m[38;5;12m(http://web.stanford.edu/class/cs20si/syllabus.html)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;14m[1mUnofficial[0m[38;5;14m[1m [0m[38;5;14m[1mVideos[0m[38;5;12m [39m
[38;5;12m(https://youtu.be/g-EvyKpZjmQ?list=PLSPPwKHXGS2110rEaNH7amFGmaD5hsObs)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow World[0m[38;5;12m (https://github.com/astorfi/TensorFlow-World) - Concise and ready-to-use TensorFlow tutorials with detailed documentation are provided.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mEffective Tensorflow[0m[38;5;12m (https://github.com/vahidk/EffectiveTensorflow) - TensorFlow howtos and best practices. Covers the basics as well as advanced topics.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorLayer[0m[38;5;12m (http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html) - Modular implementation for TensorFlow's official tutorials. ([39m[38;5;14m[1mCN[0m[38;5;12m (https://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html)).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mUnderstanding The Tensorflow Estimator API[0m[38;5;12m (https://www.lighttag.io/blog/tensorflow-estimator-api/) A conceptual overview of the Estimator API, when you'd use it and why. [39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mIntroduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning[0m[38;5;12m (https://www.coursera.org/learn/introduction-tensorflow) - Introduction to Tensorflow offered by Coursera[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mConvolutional Neural Networks in TensorFlow[0m[38;5;12m (https://www.coursera.org/learn/convolutional-neural-networks-tensorflow) - Convolutional Neural Networks in Tensorflow, offered by Coursera[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorLayerX[0m[38;5;12m (https://tensorlayerx.readthedocs.io/en/latest/index.html#user-guide) - Using TensorFlow like PyTorch. ([39m[38;5;14m[1mApi docs[0m[38;5;12m (https://tensorlayerx.readthedocs.io/en/latest/index.html#))[39m



[38;2;255;187;0m[4mModels/Projects[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorflow-Project-Template[0m[38;5;12m (https://github.com/Mrgemy95/Tensorflow-Project-Template) - A simple and well-designed template for your tensorflow project.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDomain Transfer Network[0m[38;5;12m (https://github.com/yunjey/dtn-tensorflow) - Implementation of Unsupervised Cross-Domain Image Generation[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mShow, Attend and Tell[0m[38;5;12m (https://github.com/yunjey/show_attend_and_tell) - Attention Based Image Caption Generator[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNeural Style[0m[38;5;12m (https://github.com/cysmith/neural-style-tf) Implementation of Neural Style[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSRGAN[0m[38;5;12m (https://github.com/tensorlayer/srgan) - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mPretty Tensor[0m[38;5;12m (https://github.com/google/prettytensor) - Pretty Tensor provides a high level builder API[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNeural Style[0m[38;5;12m (https://github.com/anishathalye/neural-style) - An implementation of neural style[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mAlexNet3D[0m[38;5;12m (https://github.com/denti/AlexNet3D) - An implementations of AlexNet3D. Simple AlexNet model but with 3D convolutional layers (conv3d).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow White Paper Notes[0m[38;5;12m (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[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNeuralArt[0m[38;5;12m (https://github.com/ckmarkoh/neuralart_tensorflow) - Implementation of A Neural Algorithm of Artistic Style[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGenerative Handwriting Demo using TensorFlow[0m[38;5;12m (https://github.com/hardmaru/write-rnn-tensorflow) - An attempt to implement the random handwriting generation portion of Alex Graves' paper[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNeural Turing Machine in TensorFlow[0m[38;5;12m (https://github.com/carpedm20/NTM-tensorflow) - implementation of Neural Turing Machine[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGoogleNet Convolutional Neural Network Groups Movie Scenes By Setting[0m[38;5;12m (https://github.com/agermanidis/thingscoop) - Search, filter, and describe videos based on objects, places, and other things that appear in them[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNeural machine translation between the writings of Shakespeare and modern English using TensorFlow[0m
[38;5;12m (https://github.com/tokestermw/tensorflow-shakespeare) - This performs a monolingual translation, going from modern English to Shakespeare and vice-versa.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mChatbot[0m[38;5;12m (https://github.com/Conchylicultor/DeepQA) - Implementation of [39m[38;5;14m[1m"A neural conversational model"[0m[38;5;12m (http://arxiv.org/abs/1506.05869)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSeq2seq-Chatbot[0m[38;5;12m (https://github.com/tensorlayer/seq2seq-chatbot) - Chatbot in 200 lines of code[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDCGAN[0m[38;5;12m (https://github.com/tensorlayer/dcgan) - Deep Convolutional Generative Adversarial Networks[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGAN-CLS[0m[38;5;12m (https://github.com/zsdonghao/text-to-image) -Generative Adversarial Text to Image Synthesis[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mim2im[0m[38;5;12m (https://github.com/zsdonghao/Unsup-Im2Im) - Unsupervised Image to Image Translation with Generative Adversarial Networks[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mImproved CycleGAN[0m[38;5;12m (https://github.com/luoxier/CycleGAN_Tensorlayer) - Unpaired Image to Image Translation[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDAGAN[0m[38;5;12m (https://github.com/nebulaV/DAGAN) - Fast Compressed Sensing MRI Reconstruction[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mColornet - Neural Network to colorize grayscale images[0m[38;5;12m (https://github.com/pavelgonchar/colornet) - Neural Network to colorize grayscale images[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNeural Caption Generator[0m[38;5;12m (https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow) - Implementation of [39m[38;5;14m[1m"Show and Tell"[0m[38;5;12m (http://arxiv.org/abs/1411.4555)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNeural Caption Generator with Attention[0m[38;5;12m (https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow) - Implementation of [39m[38;5;14m[1m"Show, Attend and Tell"[0m[38;5;12m (http://arxiv.org/abs/1502.03044)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mWeakly_detector[0m[38;5;12m (https://github.com/jazzsaxmafia/Weakly_detector) - Implementation of [39m[38;5;14m[1m"Learning Deep Features for Discriminative Localization"[0m[38;5;12m (http://cnnlocalization.csail.mit.edu/)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDynamic Capacity Networks[0m[38;5;12m (https://github.com/jazzsaxmafia/dcn.tf) - Implementation of [39m[38;5;14m[1m"Dynamic Capacity Networks"[0m[38;5;12m (http://arxiv.org/abs/1511.07838)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mHMM in TensorFlow[0m[38;5;12m (https://github.com/dwiel/tensorflow_hmm) - Implementation of viterbi and forward/backward algorithms for HMM[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDeepOSM[0m[38;5;12m (https://github.com/trailbehind/DeepOSM) - Train TensorFlow neural nets with OpenStreetMap features and satellite imagery.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDQN-tensorflow[0m[38;5;12m (https://github.com/devsisters/DQN-tensorflow) - TensorFlow implementation of DeepMind's 'Human-Level Control through Deep Reinforcement Learning' with OpenAI Gym by Devsisters.com[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mPolicy Gradient[0m[38;5;12m (https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_atari_pong.py) - For Playing Atari Ping Pong[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDeep Q-Network[0m[38;5;12m (https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_frozenlake_dqn.py) - For Playing Frozen Lake Game[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mAC[0m[38;5;12m (https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_cartpole_ac.py) - Actor Critic for Playing Discrete Action space Game (Cartpole)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mA3C[0m[38;5;12m (https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_bipedalwalker_a3c_continuous_action.py) - Asynchronous Advantage Actor Critic (A3C) for Continuous Action Space (Bipedal Walker)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDAGGER[0m[38;5;12m (https://github.com/zsdonghao/Imitation-Learning-Dagger-Torcs) - For Playing [39m[38;5;14m[1mGym Torcs[0m[38;5;12m (https://github.com/ugo-nama-kun/gym_torcs)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTRPO[0m[38;5;12m (https://github.com/jjkke88/RL_toolbox) - For Continuous and Discrete Action Space by[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mHighway[0m[38;5;14m[1m [0m[38;5;14m[1mNetwork[0m[38;5;12m [39m[38;5;12m(https://github.com/fomorians/highway-cnn)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mimplementation[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;14m[1m"Training[0m[38;5;14m[1m [0m[38;5;14m[1mVery[0m[38;5;14m[1m [0m[38;5;14m[1mDeep[0m[38;5;14m[1m [0m[38;5;14m[1mNetworks"[0m[38;5;12m [39m[38;5;12m(http://arxiv.org/abs/1507.06228)[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;12ma[39m[38;5;12m [39m[38;5;14m[1mblog[0m[38;5;14m[1m [0m[38;5;14m[1mpost[0m[38;5;12m [39m
[38;5;12m(https://medium.com/jim-fleming/highway-networks-with-tensorflow-1e6dfa667daa#.ndicn1i27)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mHierarchical[0m[38;5;14m[1m [0m[38;5;14m[1mAttention[0m[38;5;14m[1m [0m[38;5;14m[1mNetworks[0m[38;5;12m [39m[38;5;12m(https://github.com/tqtg/hierarchical-attention-networks)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mimplementation[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;14m[1m"Hierarchical[0m[38;5;14m[1m [0m[38;5;14m[1mAttention[0m[38;5;14m[1m [0m[38;5;14m[1mNetworks[0m[38;5;14m[1m [0m[38;5;14m[1mfor[0m[38;5;14m[1m [0m[38;5;14m[1mDocument[0m[38;5;14m[1m [0m[38;5;14m[1mClassification"[0m[38;5;12m [39m
[38;5;12m(https://www.cs.cmu.edu/~hovy/papers/16HLT-hierarchical-attention-networks.pdf)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSentence[0m[38;5;14m[1m [0m[38;5;14m[1mClassification[0m[38;5;14m[1m [0m[38;5;14m[1mwith[0m[38;5;14m[1m [0m[38;5;14m[1mCNN[0m[38;5;12m [39m[38;5;12m(https://github.com/dennybritz/cnn-text-classification-tf)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mimplementation[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;14m[1m"Convolutional[0m[38;5;14m[1m [0m[38;5;14m[1mNeural[0m[38;5;14m[1m [0m[38;5;14m[1mNetworks[0m[38;5;14m[1m [0m[38;5;14m[1mfor[0m[38;5;14m[1m [0m[38;5;14m[1mSentence[0m[38;5;14m[1m [0m[38;5;14m[1mClassification"[0m[38;5;12m [39m[38;5;12m(http://arxiv.org/abs/1408.5882)[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;12ma[39m[38;5;12m [39m[38;5;14m[1mblog[0m[38;5;14m[1m [0m[38;5;14m[1mpost[0m[38;5;12m [39m
[38;5;12m(http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mEnd-To-End Memory Networks[0m[38;5;12m (https://github.com/domluna/memn2n) - Implementation of [39m[38;5;14m[1mEnd-To-End Memory Networks[0m[38;5;12m (http://arxiv.org/abs/1503.08895)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCharacter-Aware Neural Language Models[0m[38;5;12m (https://github.com/carpedm20/lstm-char-cnn-tensorflow) - TensorFlow implementation of [39m[38;5;14m[1mCharacter-Aware Neural Language Models[0m[38;5;12m (http://arxiv.org/abs/1508.06615)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mYOLO TensorFlow ++[0m[38;5;12m (https://github.com/thtrieu/yolotf) - TensorFlow implementation of 'YOLO: Real-Time Object Detection', with training and an actual support for real-time running on mobile devices.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mWavenet[0m[38;5;12m (https://github.com/ibab/tensorflow-wavenet) - This is a TensorFlow implementation of the [39m[38;5;14m[1mWaveNet generative neural network architecture[0m[38;5;12m (https://deepmind.com/blog/wavenet-generative-model-raw-audio/) for audio generation.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMnemonic[0m[38;5;14m[1m [0m[38;5;14m[1mDescent[0m[38;5;14m[1m [0m[38;5;14m[1mMethod[0m[38;5;12m [39m[38;5;12m(https://github.com/trigeorgis/mdm)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mTensorflow[39m[38;5;12m [39m[38;5;12mimplementation[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;14m[1m"Mnemonic[0m[38;5;14m[1m [0m[38;5;14m[1mDescent[0m[38;5;14m[1m [0m[38;5;14m[1mMethod:[0m[38;5;14m[1m [0m[38;5;14m[1mA[0m[38;5;14m[1m [0m[38;5;14m[1mrecurrent[0m[38;5;14m[1m [0m[38;5;14m[1mprocess[0m[38;5;14m[1m [0m[38;5;14m[1mapplied[0m[38;5;14m[1m [0m[38;5;14m[1mfor[0m[38;5;14m[1m [0m[38;5;14m[1mend-to-end[0m[38;5;14m[1m [0m[38;5;14m[1mface[0m[38;5;14m[1m [0m[38;5;14m[1malignment"[0m[38;5;12m [39m
[38;5;12m(http://ibug.doc.ic.ac.uk/media/uploads/documents/trigeorgis2016mnemonic.pdf)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCNN visualization using Tensorflow[0m[38;5;12m (https://github.com/InFoCusp/tf_cnnvis) - Tensorflow implementation of [39m[38;5;14m[1m"Visualizing and Understanding Convolutional Networks"[0m[38;5;12m (https://www.cs.nyu.edu/~fergus/papers/zeilerECCV2014.pdf)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mVGAN Tensorflow[0m[38;5;12m (https://github.com/Singularity42/VGAN-Tensorflow) - Tensorflow implementation for MIT [39m[38;5;14m[1m"Generating Videos with Scene Dynamics"[0m[38;5;12m (http://carlvondrick.com/tinyvideo/) by Vondrick et al.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m3D[0m[38;5;14m[1m [0m[38;5;14m[1mConvolutional[0m[38;5;14m[1m [0m[38;5;14m[1mNeural[0m[38;5;14m[1m [0m[38;5;14m[1mNetworks[0m[38;5;14m[1m [0m[38;5;14m[1min[0m[38;5;14m[1m [0m[38;5;14m[1mTensorFlow[0m[38;5;12m [39m[38;5;12m(https://github.com/astorfi/3D-convolutional-speaker-recognition)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mImplementation[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;14m[1m"3D[0m[38;5;14m[1m [0m[38;5;14m[1mConvolutional[0m[38;5;14m[1m [0m[38;5;14m[1mNeural[0m[38;5;14m[1m [0m[38;5;14m[1mNetworks[0m[38;5;14m[1m [0m[38;5;14m[1mfor[0m[38;5;14m[1m [0m[38;5;14m[1mSpeaker[0m[38;5;14m[1m [0m[38;5;14m[1mVerification[0m[38;5;14m[1m [0m[38;5;14m[1mapplication"[0m[38;5;12m [39m
[38;5;12m(https://arxiv.org/abs/1705.09422)[39m[38;5;12m [39m[38;5;12min[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mTorfi[39m[38;5;12m [39m[38;5;12met[39m[38;5;12m [39m[38;5;12mal.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mU-Net[0m[38;5;12m (https://github.com/zsdonghao/u-net-brain-tumor) - For Brain Tumor Segmentation[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSpatial Transformer Networks[0m[38;5;12m (https://github.com/zsdonghao/Spatial-Transformer-Nets) - Learn the Transformation Function [39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLip[0m[38;5;14m[1m [0m[38;5;14m[1mReading[0m[38;5;14m[1m [0m[38;5;14m[1m-[0m[38;5;14m[1m [0m[38;5;14m[1mCross[0m[38;5;14m[1m [0m[38;5;14m[1mAudio-Visual[0m[38;5;14m[1m [0m[38;5;14m[1mRecognition[0m[38;5;14m[1m [0m[38;5;14m[1musing[0m[38;5;14m[1m [0m[38;5;14m[1m3D[0m[38;5;14m[1m [0m[38;5;14m[1mArchitectures[0m[38;5;14m[1m [0m[38;5;14m[1min[0m[38;5;14m[1m [0m[38;5;14m[1mTensorFlow[0m[38;5;12m [39m[38;5;12m(https://github.com/astorfi/lip-reading-deeplearning)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mImplementation[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;14m[1m"Cross[0m[38;5;14m[1m [0m[38;5;14m[1mAudio-Visual[0m[38;5;14m[1m [0m[38;5;14m[1mRecognition[0m[38;5;14m[1m [0m[38;5;14m[1min[0m[38;5;14m[1m [0m[38;5;14m[1mthe[0m[38;5;14m[1m [0m[38;5;14m[1mWild[0m[38;5;14m[1m [0m[38;5;14m[1mUsing[0m[38;5;14m[1m [0m[38;5;14m[1mDeep[0m[38;5;14m[1m [0m[38;5;14m[1mLearning"[0m[38;5;12m [39m
[38;5;12m(https://arxiv.org/abs/1706.05739)[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mTorfi[39m[38;5;12m [39m[38;5;12met[39m[38;5;12m [39m[38;5;12mal.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mAttentive Object Tracking[0m[38;5;12m (https://github.com/akosiorek/hart) - Implementation of [39m[38;5;14m[1m"Hierarchical Attentive Recurrent Tracking"[0m[38;5;12m (https://arxiv.org/abs/1706.09262)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mHolographic Embeddings for Graph Completion and Link Prediction[0m[38;5;12m (https://github.com/laxatives/TensorFlow-TransX) - Implementation of [39m[38;5;14m[1mHolographic Embeddings of Knowledge Graphs[0m[38;5;12m (http://arxiv.org/abs/1510.04935)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mUnsupervised Object Counting[0m[38;5;12m (https://github.com/akosiorek/attend_infer_repeat) - Implementation of [39m[38;5;14m[1m"Attend, Infer, Repeat"[0m[38;5;12m (https://papers.nips.cc/paper/6230-attend-infer-repeat-fast-scene-understanding-with-generative-models)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorflow FastText[0m[38;5;12m (https://github.com/apcode/tensorflow_fasttext) - A simple embedding based text classifier inspired by Facebook's fastText.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMusicGenreClassification[0m[38;5;12m (https://github.com/mlachmish/MusicGenreClassification) - Classify music genre from a 10 second sound stream using a Neural Network.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mKubeflow[0m[38;5;12m (https://github.com/kubeflow/kubeflow) - Framework for easily using Tensorflow with Kubernetes.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorNets[0m[38;5;12m (https://github.com/taehoonlee/tensornets) - 40+ Popular Computer Vision Models With Pre-trained Weights.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLadder Network[0m[38;5;12m (https://github.com/divamgupta/ladder_network_keras) - Implementation of Ladder Network for Semi-Supervised Learning in Keras and Tensorflow[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTF-Unet[0m[38;5;12m (https://github.com/juniorxsound/TF-Unet) - General purpose U-Network implemented in Keras for image segmentation[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSarus[0m[38;5;14m[1m [0m[38;5;14m[1mTF2[0m[38;5;14m[1m [0m[38;5;14m[1mModels[0m[38;5;12m [39m[38;5;12m(https://github.com/sarus-tech/tf2-published-models)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mA[39m[38;5;12m [39m[38;5;12mlong[39m[38;5;12m [39m[38;5;12mlist[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mrecent[39m[38;5;12m [39m[38;5;12mgenerative[39m[38;5;12m [39m[38;5;12mmodels[39m[38;5;12m [39m[38;5;12mimplemented[39m[38;5;12m [39m[38;5;12min[39m[38;5;12m [39m[38;5;12mclean,[39m[38;5;12m [39m[38;5;12measy[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12mreuse,[39m[38;5;12m [39m[38;5;12mTensorflow[39m[38;5;12m [39m[38;5;12m2[39m[38;5;12m [39m[38;5;12mcode[39m[38;5;12m [39m[38;5;12m(Plain[39m[38;5;12m [39m[38;5;12mAutoencoder,[39m[38;5;12m [39m[38;5;12mVAE,[39m[38;5;12m [39m[38;5;12mVQ-VAE,[39m[38;5;12m [39m[38;5;12mPixelCNN,[39m[38;5;12m [39m[38;5;12mGated[39m[38;5;12m [39m[38;5;12mPixelCNN,[39m[38;5;12m [39m
[38;5;12mPixelCNN++,[39m[38;5;12m [39m[38;5;12mPixelSNAIL,[39m[38;5;12m [39m[38;5;12mConditional[39m[38;5;12m [39m[38;5;12mNeural[39m[38;5;12m [39m[38;5;12mProcesses).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mModel[0m[38;5;14m[1m [0m[38;5;14m[1mMaker[0m[38;5;12m [39m[38;5;12m(https://www.tensorflow.org/lite/guide/model_maker)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mA[39m[38;5;12m [39m[38;5;12mtransfer[39m[38;5;12m [39m[38;5;12mlearning[39m[38;5;12m [39m[38;5;12mlibrary[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m[38;5;12msimplifies[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mprocess[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mtraining,[39m[38;5;12m [39m[38;5;12mevaluation[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mdeployment[39m[38;5;12m [39m[38;5;12mfor[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mLite[39m[38;5;12m [39m[38;5;12mmodels[39m[38;5;12m [39m[38;5;12m(support:[39m[38;5;12m [39m[38;5;12mImage[39m[38;5;12m [39m[38;5;12mClassification,[39m[38;5;12m [39m[38;5;12mObject[39m[38;5;12m [39m
[38;5;12mDetection,[39m[38;5;12m [39m[38;5;12mText[39m[38;5;12m [39m[38;5;12mClassification,[39m[38;5;12m [39m[38;5;12mBERT[39m[38;5;12m [39m[38;5;12mQuestion[39m[38;5;12m [39m[38;5;12mAnswer,[39m[38;5;12m [39m[38;5;12mAudio[39m[38;5;12m [39m[38;5;12mClassification,[39m[38;5;12m [39m[38;5;12mRecommendation[39m[38;5;12m [39m[38;5;12metc.;[39m[38;5;12m [39m[38;5;14m[1mAPI[0m[38;5;14m[1m [0m[38;5;14m[1mreference[0m[38;5;12m [39m[38;5;12m(https://www.tensorflow.org/lite/api_docs/python/tflite_model_maker)).[39m




[38;2;255;187;0m[4mPowered by TensorFlow[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mYOLO TensorFlow[0m[38;5;12m (https://github.com/gliese581gg/YOLO_tensorflow) - Implementation of 'YOLO : Real-Time Object Detection'[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mandroid-yolo[0m[38;5;12m (https://github.com/natanielruiz/android-yolo) - Real-time object detection on Android using the YOLO network, powered by TensorFlow.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMagenta[0m[38;5;12m (https://github.com/tensorflow/magenta) - Research project to advance the state of the art in machine intelligence for music and art generation[39m




[38;2;255;187;0m[4mLibraries[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Estimators[0m[38;5;12m (https://www.tensorflow.org/guide/estimators) - high-level TensorFlow API that greatly simplifies machine learning programming (originally [39m[38;5;14m[1mtensorflow/skflow[0m[38;5;12m (https://github.com/tensorflow/skflow))[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Interface to TensorFlow[0m[38;5;12m (https://tensorflow.rstudio.com/) - R interface to TensorFlow APIs, including Estimators, Keras, Datasets, etc.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLattice[0m[38;5;12m (https://github.com/tensorflow/lattice) - Implementation of Monotonic Calibrated Interpolated Look-Up Tables in TensorFlow[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtensorflow.rb[0m[38;5;12m (https://github.com/somaticio/tensorflow.rb) - TensorFlow native interface for ruby using SWIG[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtflearn[0m[38;5;12m (https://github.com/tflearn/tflearn) - Deep learning library featuring a higher-level API[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorLayer[0m[38;5;12m (https://github.com/tensorlayer/tensorlayer) - Deep learning and reinforcement learning library for researchers and engineers[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow-Slim[0m[38;5;12m (https://github.com/tensorflow/models/tree/master/inception/inception/slim) - High-level library for defining models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFrames[0m[38;5;12m (https://github.com/tjhunter/tensorframes) - TensorFlow binding for Apache Spark[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorForce[0m[38;5;12m (https://github.com/reinforceio/tensorforce) - TensorForce: A TensorFlow library for applied reinforcement learning[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlowOnSpark[0m[38;5;12m (https://github.com/yahoo/TensorFlowOnSpark) - initiative from Yahoo! to enable distributed TensorFlow with Apache Spark.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcaffe-tensorflow[0m[38;5;12m (https://github.com/ethereon/caffe-tensorflow) - Convert Caffe models to TensorFlow format[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mkeras[0m[38;5;12m (http://keras.io) - Minimal, modular deep learning library for TensorFlow and Theano[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSyntaxNet:[0m[38;5;14m[1m [0m[38;5;14m[1mNeural[0m[38;5;14m[1m [0m[38;5;14m[1mModels[0m[38;5;14m[1m [0m[38;5;14m[1mof[0m[38;5;14m[1m [0m[38;5;14m[1mSyntax[0m[38;5;12m [39m[38;5;12m(https://github.com/tensorflow/models/tree/master/syntaxnet)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mA[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mimplementation[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mmodels[39m[38;5;12m [39m[38;5;12mdescribed[39m[38;5;12m [39m[38;5;12min[39m[38;5;12m [39m[38;5;14m[1mGlobally[0m[38;5;14m[1m [0m[38;5;14m[1mNormalized[0m[38;5;14m[1m [0m[38;5;14m[1mTransition-Based[0m[38;5;14m[1m [0m[38;5;14m[1mNeural[0m[38;5;14m[1m [0m[38;5;14m[1mNetworks,[0m[38;5;14m[1m [0m[38;5;14m[1mAndor[0m[38;5;14m[1m [0m[38;5;14m[1met[0m[38;5;14m[1m [0m[38;5;14m[1mal.[0m[38;5;14m[1m [0m[38;5;14m[1m(2016)[0m[38;5;12m [39m
[38;5;12m(http://arxiv.org/pdf/1603.06042.pdf)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mkeras-js[0m[38;5;12m (https://github.com/transcranial/keras-js) - Run Keras models (tensorflow backend) in the browser, with GPU support[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNNFlow[0m[38;5;12m (https://github.com/welschma/NNFlow) - Simple framework allowing to read-in ROOT NTuples by converting them to a Numpy array and then use them in Google Tensorflow.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSonnet[0m[38;5;12m (https://github.com/deepmind/sonnet) - Sonnet is DeepMind's library built on top of TensorFlow for building complex neural networks.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtensorpack[0m[38;5;12m (https://github.com/ppwwyyxx/tensorpack) - Neural Network Toolbox on TensorFlow focusing on training speed and on large datasets.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtf-encrypted[0m[38;5;12m (https://github.com/mortendahl/tf-encrypted) - Layer on top of TensorFlow for doing machine learning on encrypted data[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpytorch2keras[0m[38;5;12m (https://github.com/nerox8664/pytorch2keras) - Convert PyTorch models to Keras (with TensorFlow backend) format[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgluon2keras[0m[38;5;12m (https://github.com/stjordanis/gluon2keras) - Convert Gluon models to Keras (with TensorFlow backend) format[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorIO[0m[38;5;12m (https://doc-ai.github.io/tensorio/) - Lightweight, cross-platform library for deploying TensorFlow Lite models to mobile devices. [39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mStellarGraph[0m[38;5;12m (https://github.com/stellargraph/stellargraph) - Machine Learning on Graphs, a Python library for machine learning on graph-structured (network-structured) data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDeepBay[0m[38;5;12m (https://github.com/ElPapi42/DeepBay) - High-Level Keras Complement for implement common architectures stacks, served as easy to use plug-n-play modules[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorflow-Probability[0m[38;5;12m (https://www.tensorflow.org/probability) - Probabalistic programming built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorLayerX[0m[38;5;12m (https://github.com/tensorlayer/TensorLayerX) - TensorLayerX: A Unified Deep Learning Framework for All Hardwares, Backends and OS, including TensorFlow.[39m



[38;2;255;187;0m[4mTools/Utilities[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSpeedster[0m[38;5;12m (https://github.com/nebuly-ai/nebullvm/tree/main/apps/accelerate/speedster) - Automatically apply SOTA optimization techniques to achieve the maximum inference speed-up on your hardware.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGuild AI[0m[38;5;12m (https://guild.ai) - Task runner and package manager for TensorFlow[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mML Workspace[0m[38;5;12m (https://github.com/ml-tooling/ml-workspace) - All-in-one web IDE for machine learning and data science. Combines Tensorflow, Jupyter, VS Code, Tensorboard, and many other tools/libraries into one Docker image.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcreate-tf-app[0m[38;5;12m (https://github.com/radi-cho/create-tf-app) - Project builder command line tool for Tensorflow covering environment management, linting, and logging.[39m



[38;2;255;187;0m[4mVideos[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Guide 1[0m[38;5;12m (http://bit.ly/1OX8s8Y) - A guide to installation and use[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Guide 2[0m[38;5;12m (http://bit.ly/1R27Ki9) - Continuation of first video[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Basic Usage[0m[38;5;12m (http://bit.ly/1TCNmEY) - A guide going over basic usage[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Deep MNIST for Experts[0m[38;5;12m (http://bit.ly/1L9IfJx) - Goes over Deep MNIST[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Udacity Deep Learning[0m[38;5;12m (https://www.youtube.com/watch?v=ReaxoSIM5XQ) - Basic steps to install TensorFlow for free on the Cloud 9 online service with 1Gb of data[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mWhy Google wants everyone to have access to TensorFlow[0m[38;5;12m (http://video.foxnews.com/v/4611174773001/why-google-wants-everyone-to-have-access-to-tensorflow/?#sp=show-clips)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mVideos from TensorFlow Silicon Valley Meet Up 1/19/2016[0m[38;5;12m (http://blog.altoros.com/videos-from-tensorflow-silicon-valley-meetup-january-19-2016.html)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mVideos from TensorFlow Silicon Valley Meet Up 1/21/2016[0m[38;5;12m (http://blog.altoros.com/videos-from-tensorflow-seattle-meetup-jan-21-2016.html)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mStanford CS224d Lecture 7 - Introduction to TensorFlow, 19th Apr 2016[0m
[38;5;12m (https://www.youtube.com/watch?v=L8Y2_Cq2X5s&index=7&list=PLmImxx8Char9Ig0ZHSyTqGsdhb9weEGam) - CS224d Deep Learning for Natural Language Processing by Richard Socher[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDiving[0m[38;5;14m[1m [0m[38;5;14m[1minto[0m[38;5;14m[1m [0m[38;5;14m[1mMachine[0m[38;5;14m[1m [0m[38;5;14m[1mLearning[0m[38;5;14m[1m [0m[38;5;14m[1mthrough[0m[38;5;14m[1m [0m[38;5;14m[1mTensorFlow[0m[38;5;12m [39m[38;5;12m(https://youtu.be/GZBIPwdGtkk?list=PLBkISg6QfSX9HL6us70IBs9slFciFFa4W)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mPycon[39m[38;5;12m [39m[38;5;12m2016[39m[38;5;12m [39m[38;5;12mPortland[39m[38;5;12m [39m[38;5;12mOregon,[39m[38;5;12m [39m[38;5;14m[1mSlide[0m[38;5;12m [39m[38;5;12m(https://storage.googleapis.com/amy-jo/talks/tf-workshop.pdf)[39m[38;5;12m [39m[38;5;12m&[39m[38;5;12m [39m[38;5;14m[1mCode[0m[38;5;12m [39m
[38;5;12m(https://github.com/amygdala/tensorflow-workshop)[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mJulia[39m[38;5;12m [39m[38;5;12mFerraioli,[39m[38;5;12m [39m[38;5;12mAmy[39m[38;5;12m [39m[38;5;12mUnruh,[39m[38;5;12m [39m[38;5;12mEli[39m[38;5;12m [39m[38;5;12mBixby[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLarge Scale Deep Learning with TensorFlow[0m[38;5;12m (https://youtu.be/XYwIDn00PAo) - Spark Summit 2016 Keynote by Jeff Dean[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorflow and deep learning - without at PhD[0m[38;5;12m (https://www.youtube.com/watch?v=vq2nnJ4g6N0) -  by Martin Görner[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorflow and deep learning - without at PhD, Part 2 (Google Cloud Next '17)[0m[38;5;12m (https://www.youtube.com/watch?v=fTUwdXUFfI8) -  by Martin Görner[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mImage recognition in Go using TensorFlow[0m[38;5;12m (https://youtu.be/P8MZ1Z2LHrw) -  by Alex Pliutau[39m





[38;2;255;187;0m[4mPapers[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems[0m
[38;5;12m (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[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks[0m[38;5;12m (https://arxiv.org/pdf/1708.02637.pdf)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTF.Learn: TensorFlow's High-level Module for Distributed Machine Learning[0m[38;5;12m (https://arxiv.org/abs/1612.04251)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mComparative[0m[38;5;14m[1m [0m[38;5;14m[1mStudy[0m[38;5;14m[1m [0m[38;5;14m[1mof[0m[38;5;14m[1m [0m[38;5;14m[1mDeep[0m[38;5;14m[1m [0m[38;5;14m[1mLearning[0m[38;5;14m[1m [0m[38;5;14m[1mSoftware[0m[38;5;14m[1m [0m[38;5;14m[1mFrameworks[0m[38;5;12m [39m[38;5;12m(http://arxiv.org/abs/1511.06435)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mThe[39m[38;5;12m [39m[38;5;12mstudy[39m[38;5;12m [39m[38;5;12mis[39m[38;5;12m [39m[38;5;12mperformed[39m[38;5;12m [39m[38;5;12mon[39m[38;5;12m [39m[38;5;12mseveral[39m[38;5;12m [39m[38;5;12mtypes[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mdeep[39m[38;5;12m [39m[38;5;12mlearning[39m[38;5;12m [39m[38;5;12marchitectures[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mwe[39m[38;5;12m [39m[38;5;12mevaluate[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mperformance[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mabove[39m[38;5;12m [39m[38;5;12mframeworks[39m[38;5;12m [39m[38;5;12mwhen[39m[38;5;12m [39m[38;5;12memployed[39m[38;5;12m [39m[38;5;12mon[39m
[38;5;12ma[39m[38;5;12m [39m[38;5;12msingle[39m[38;5;12m [39m[38;5;12mmachine[39m[38;5;12m [39m[38;5;12mfor[39m[38;5;12m [39m[38;5;12mboth[39m[38;5;12m [39m[38;5;12m(multi-threaded)[39m[38;5;12m [39m[38;5;12mCPU[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mGPU[39m[38;5;12m [39m[38;5;12m(Nvidia[39m[38;5;12m [39m[38;5;12mTitan[39m[38;5;12m [39m[38;5;12mX)[39m[38;5;12m [39m[38;5;12msettings[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDistributed TensorFlow with MPI[0m[38;5;12m (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)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGlobally Normalized Transition-Based Neural Networks[0m[38;5;12m (http://arxiv.org/abs/1603.06042) - This paper describes the models behind [39m[38;5;14m[1mSyntaxNet[0m[38;5;12m (https://github.com/tensorflow/models/tree/master/syntaxnet).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow: A system for large-scale machine learning[0m[38;5;12m (https://arxiv.org/abs/1605.08695) - This paper describes the TensorFlow dataflow model in contrast to existing systems and demonstrate the compelling performance[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorLayer:[0m[38;5;14m[1m [0m[38;5;14m[1mA[0m[38;5;14m[1m [0m[38;5;14m[1mVersatile[0m[38;5;14m[1m [0m[38;5;14m[1mLibrary[0m[38;5;14m[1m [0m[38;5;14m[1mfor[0m[38;5;14m[1m [0m[38;5;14m[1mEfficient[0m[38;5;14m[1m [0m[38;5;14m[1mDeep[0m[38;5;14m[1m [0m[38;5;14m[1mLearning[0m[38;5;14m[1m [0m[38;5;14m[1mDevelopment[0m[38;5;12m [39m[38;5;12m(https://arxiv.org/abs/1707.08551)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mThis[39m[38;5;12m [39m[38;5;12mpaper[39m[38;5;12m [39m[38;5;12mdescribes[39m[38;5;12m [39m[38;5;12ma[39m[38;5;12m [39m[38;5;12mversatile[39m[38;5;12m [39m[38;5;12mPython[39m[38;5;12m [39m[38;5;12mlibrary[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m[38;5;12maims[39m[38;5;12m [39m[38;5;12mat[39m[38;5;12m [39m[38;5;12mhelping[39m[38;5;12m [39m[38;5;12mresearchers[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mengineers[39m[38;5;12m [39m[38;5;12mefficiently[39m[38;5;12m [39m[38;5;12mdevelop[39m[38;5;12m [39m[38;5;12mdeep[39m[38;5;12m [39m
[38;5;12mlearning[39m[38;5;12m [39m[38;5;12msystems.[39m[38;5;12m [39m[38;5;12m(Winner[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mThe[39m[38;5;12m [39m[38;5;12mBest[39m[38;5;12m [39m[38;5;12mOpen[39m[38;5;12m [39m[38;5;12mSource[39m[38;5;12m [39m[38;5;12mSoftware[39m[38;5;12m [39m[38;5;12mAward[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mACM[39m[38;5;12m [39m[38;5;12mMM[39m[38;5;12m [39m[38;5;12m2017)[39m



[38;2;255;187;0m[4mOfficial announcements[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow: smarter machine learning, for everyone[0m[38;5;12m (https://googleblog.blogspot.com/2015/11/tensorflow-smarter-machine-learning-for.html) - An introduction to TensorFlow[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mAnnouncing[0m[38;5;14m[1m [0m[38;5;14m[1mSyntaxNet:[0m[38;5;14m[1m [0m[38;5;14m[1mThe[0m[38;5;14m[1m [0m[38;5;14m[1mWorld’s[0m[38;5;14m[1m [0m[38;5;14m[1mMost[0m[38;5;14m[1m [0m[38;5;14m[1mAccurate[0m[38;5;14m[1m [0m[38;5;14m[1mParser[0m[38;5;14m[1m [0m[38;5;14m[1mGoes[0m[38;5;14m[1m [0m[38;5;14m[1mOpen[0m[38;5;14m[1m [0m[38;5;14m[1mSource[0m[38;5;12m [39m[38;5;12m(http://googleresearch.blogspot.com/2016/05/announcing-syntaxnet-worlds-most.html)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mRelease[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mSyntaxNet,[39m[38;5;12m [39m[38;5;12m"an[39m[38;5;12m [39m[38;5;12mopen-source[39m[38;5;12m [39m[38;5;12mneural[39m[38;5;12m [39m[38;5;12mnetwork[39m[38;5;12m [39m[38;5;12mframework[39m[38;5;12m [39m[38;5;12mimplemented[39m[38;5;12m [39m[38;5;12min[39m
[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m[38;5;12mprovides[39m[38;5;12m [39m[38;5;12ma[39m[38;5;12m [39m[38;5;12mfoundation[39m[38;5;12m [39m[38;5;12mfor[39m[38;5;12m [39m[38;5;12mNatural[39m[38;5;12m [39m[38;5;12mLanguage[39m[38;5;12m [39m[38;5;12mUnderstanding[39m[38;5;12m [39m[38;5;12msystems.[39m

[38;2;255;187;0m[4mBlog posts[0m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mOfficial Tensorflow Blog[0m[38;5;12m (http://blog.tensorflow.org/)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mWhy TensorFlow will change the Game for AI[0m[38;5;12m (https://archive.fo/o9asj)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow for Poets[0m[38;5;12m (http://petewarden.com/2016/02/28/tensorflow-for-poets) - Goes over the implementation of TensorFlow[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mIntroduction to Scikit Flow - Simplified Interface to TensorFlow[0m[38;5;12m (http://terrytangyuan.github.io/2016/03/14/scikit-flow-intro/) - Key Features Illustrated[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mBuilding Machine Learning Estimator in TensorFlow[0m[38;5;12m (http://terrytangyuan.github.io/2016/07/08/understand-and-build-tensorflow-estimator/) - Understanding the Internals of TensorFlow Learn Estimators[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow - Not Just For Deep Learning[0m[38;5;12m (http://terrytangyuan.github.io/2016/08/06/tensorflow-not-just-deep-learning/)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mThe indico Machine Learning Team's take on TensorFlow[0m[38;5;12m (https://indico.io/blog/indico-tensorflow)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mThe Good, Bad, & Ugly of TensorFlow[0m[38;5;12m (https://indico.io/blog/the-good-bad-ugly-of-tensorflow/) - A survey of six months rapid evolution (+ tips/hacks and code to fix the ugly stuff), Dan Kuster at Indico, May 9, 2016[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mFizz Buzz in TensorFlow[0m[38;5;12m (http://joelgrus.com/2016/05/23/fizz-buzz-in-tensorflow/) - A joke by Joel Grus[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRNNs In TensorFlow, A Practical Guide And Undocumented Features[0m[38;5;12m (http://www.wildml.com/2016/08/rnns-in-tensorflow-a-practical-guide-and-undocumented-features/) - Step-by-step guide with full code examples on GitHub.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mUsing TensorBoard to Visualize Image Classification Retraining in TensorFlow[0m[38;5;12m (http://maxmelnick.com/2016/07/04/visualizing-tensorflow-retrain.html)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTFRecords Guide[0m[38;5;12m (http://warmspringwinds.github.io/tensorflow/tf-slim/2016/12/21/tfrecords-guide/) semantic segmentation and handling the TFRecord file format.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow Android Guide[0m[38;5;12m (https://blog.mindorks.com/android-tensorflow-machine-learning-example-ff0e9b2654cc) - Android TensorFlow Machine Learning Example.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow[0m[38;5;14m[1m [0m[38;5;14m[1mOptimizations[0m[38;5;14m[1m [0m[38;5;14m[1mon[0m[38;5;14m[1m [0m[38;5;14m[1mModern[0m[38;5;14m[1m [0m[38;5;14m[1mIntel®[0m[38;5;14m[1m [0m[38;5;14m[1mArchitecture[0m[38;5;12m [39m[38;5;12m(https://software.intel.com/en-us/articles/tensorflow-optimizations-on-modern-intel-architecture)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mIntroduces[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12moptimizations[39m[38;5;12m [39m[38;5;12mon[39m[38;5;12m [39m[38;5;12mIntel®[39m[38;5;12m [39m[38;5;12mXeon®[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mIntel®[39m[38;5;12m [39m[38;5;12mXeon[39m[38;5;12m [39m[38;5;12mPhi™[39m[38;5;12m [39m
[38;5;12mprocessor-based[39m[38;5;12m [39m[38;5;12mplatforms[39m[38;5;12m [39m[38;5;12mbased[39m[38;5;12m [39m[38;5;12mon[39m[38;5;12m [39m[38;5;12man[39m[38;5;12m [39m[38;5;12mIntel/Google[39m[38;5;12m [39m[38;5;12mcollaboration.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCoca-Cola's Image Recognition App[0m[38;5;12m (https://developers.googleblog.com/2017/09/how-machine-learning-with-tensorflow.html) Coca-Cola's product code image recognizing neural network with user input feedback loop.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mHow Does The TensorFlow Work[0m[38;5;12m (https://www.letslearnai.com/2018/02/02/how-does-the-machine-learning-library-tensorflow-work.html) How Does The Machine Learning Library TensorFlow Work?[39m




[38;2;255;187;0m[4mCommunity[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mStack Overflow[0m[38;5;12m (http://stackoverflow.com/questions/tagged/tensorflow)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m@TensorFlow on Twitter[0m[38;5;12m (https://twitter.com/tensorflow)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mReddit[0m[38;5;12m (https://www.reddit.com/r/tensorflow)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMailing List[0m[38;5;12m (https://groups.google.com/a/tensorflow.org/forum/#!forum/discuss)[39m




[38;2;255;187;0m[4mBooks[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMachine Learning with TensorFlow[0m
[38;5;12m (http://tensorflowbook.com) by Nishant Shukla, computer vision researcher at UCLA and author of Haskell Data Analysis Cookbook. This book makes the math-heavy topic of ML approachable and practicle to a newcomer. [39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mFirst Contact with TensorFlow[0m[38;5;12m (http://www.jorditorres.org/first-contact-with-tensorflow/) by Jordi Torres, professor at UPC Barcelona Tech and a research manager and senior advisor at Barcelona Supercomputing Center[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDeep Learning with Python[0m[38;5;12m (https://machinelearningmastery.com/deep-learning-with-python/) - Develop Deep Learning Models on Theano and TensorFlow Using Keras by Jason Brownlee[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow for Machine Intelligence[0m
[38;5;12m (https://bleedingedgepress.com/tensor-flow-for-machine-intelligence/) - Complete guide to use TensorFlow from the basics of graph computing, to deep learning models to using it in production environments - Bleeding Edge Press[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGetting Started with TensorFlow[0m
[38;5;12m (https://www.packtpub.com/big-data-and-business-intelligence/getting-started-tensorflow) - Get up and running with the latest numerical computing library by Google and dive deeper into your data, by Giancarlo Zaccone[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mHands-On[0m[38;5;14m[1m [0m[38;5;14m[1mMachine[0m[38;5;14m[1m [0m[38;5;14m[1mLearning[0m[38;5;14m[1m [0m[38;5;14m[1mwith[0m[38;5;14m[1m [0m[38;5;14m[1mScikit-Learn[0m[38;5;14m[1m [0m[38;5;14m[1mand[0m[38;5;14m[1m [0m[38;5;14m[1mTensorFlow[0m[38;5;12m [39m[38;5;12m(http://shop.oreilly.com/product/0636920052289.do)[39m[38;5;12m [39m[38;5;12m–[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mAurélien[39m[38;5;12m [39m[38;5;12mGeron,[39m[38;5;12m [39m[38;5;12mformer[39m[38;5;12m [39m[38;5;12mlead[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mYouTube[39m[38;5;12m [39m[38;5;12mvideo[39m[38;5;12m [39m[38;5;12mclassification[39m[38;5;12m [39m[38;5;12mteam.[39m[38;5;12m [39m[38;5;12mCovers[39m[38;5;12m [39m[38;5;12mML[39m[38;5;12m [39m[38;5;12mfundamentals,[39m[38;5;12m [39m[38;5;12mtraining[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mdeploying[39m[38;5;12m [39m
[38;5;12mdeep[39m[38;5;12m [39m[38;5;12mnets[39m[38;5;12m [39m[38;5;12macross[39m[38;5;12m [39m[38;5;12mmultiple[39m[38;5;12m [39m[38;5;12mservers[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mGPUs[39m[38;5;12m [39m[38;5;12musing[39m[38;5;12m [39m[38;5;12mTensorFlow,[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mlatest[39m[38;5;12m [39m[38;5;12mCNN,[39m[38;5;12m [39m[38;5;12mRNN[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mAutoencoder[39m[38;5;12m [39m[38;5;12marchitectures,[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mReinforcement[39m[38;5;12m [39m[38;5;12mLearning[39m[38;5;12m [39m[38;5;12m(Deep[39m[38;5;12m [39m[38;5;12mQ).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mBuilding[0m[38;5;14m[1m [0m[38;5;14m[1mMachine[0m[38;5;14m[1m [0m[38;5;14m[1mLearning[0m[38;5;14m[1m [0m[38;5;14m[1mProjects[0m[38;5;14m[1m [0m[38;5;14m[1mwith[0m[38;5;14m[1m [0m[38;5;14m[1mTensorflow[0m[38;5;12m [39m[38;5;12m(https://www.packtpub.com/big-data-and-business-intelligence/building-machine-learning-projects-tensorflow)[39m[38;5;12m [39m[38;5;12m–[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mRodolfo[39m[38;5;12m [39m[38;5;12mBonnin.[39m[38;5;12m [39m[38;5;12mThis[39m[38;5;12m [39m[38;5;12mbook[39m[38;5;12m [39m[38;5;12mcovers[39m[38;5;12m [39m[38;5;12mvarious[39m[38;5;12m [39m[38;5;12mprojects[39m[38;5;12m [39m[38;5;12min[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m
[38;5;12mexpose[39m[38;5;12m [39m[38;5;12mwhat[39m[38;5;12m [39m[38;5;12mcan[39m[38;5;12m [39m[38;5;12mbe[39m[38;5;12m [39m[38;5;12mdone[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12min[39m[38;5;12m [39m[38;5;12mdifferent[39m[38;5;12m [39m[38;5;12mscenarios.[39m[38;5;12m [39m[38;5;12mThe[39m[38;5;12m [39m[38;5;12mbook[39m[38;5;12m [39m[38;5;12mprovides[39m[38;5;12m [39m[38;5;12mprojects[39m[38;5;12m [39m[38;5;12mon[39m[38;5;12m [39m[38;5;12mtraining[39m[38;5;12m [39m[38;5;12mmodels,[39m[38;5;12m [39m[38;5;12mmachine[39m[38;5;12m [39m[38;5;12mlearning,[39m[38;5;12m [39m[38;5;12mdeep[39m[38;5;12m [39m[38;5;12mlearning,[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mworking[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;12mvarious[39m[38;5;12m [39m[38;5;12mneural[39m[38;5;12m [39m[38;5;12mnetworks.[39m[38;5;12m [39m[38;5;12mEach[39m[38;5;12m [39m[38;5;12mproject[39m[38;5;12m [39m[38;5;12mis[39m[38;5;12m [39m[38;5;12man[39m[38;5;12m [39m[38;5;12mengaging[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12minsightful[39m[38;5;12m [39m
[38;5;12mexercise[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m[38;5;12mwill[39m[38;5;12m [39m[38;5;12mteach[39m[38;5;12m [39m[38;5;12myou[39m[38;5;12m [39m[38;5;12mhow[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12muse[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mshow[39m[38;5;12m [39m[38;5;12myou[39m[38;5;12m [39m[38;5;12mhow[39m[38;5;12m [39m[38;5;12mlayers[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mdata[39m[38;5;12m [39m[38;5;12mcan[39m[38;5;12m [39m[38;5;12mbe[39m[38;5;12m [39m[38;5;12mexplored[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mworking[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;12mTensors.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDeep Learning using TensorLayer[0m[38;5;12m (http://www.broadview.com.cn/book/5059) - by Hao Dong et al. This book covers both deep learning and the implmentation by using TensorFlow and TensorLayer.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTensorFlow[0m[38;5;14m[1m [0m[38;5;14m[1m2.0[0m[38;5;14m[1m [0m[38;5;14m[1min[0m[38;5;14m[1m [0m[38;5;14m[1mAction[0m[38;5;12m [39m[38;5;12m(https://www.manning.com/books/tensorflow-in-action)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mThushan[39m[38;5;12m [39m[38;5;12mGanegedara.[39m[38;5;12m [39m[38;5;12mThis[39m[38;5;12m [39m[38;5;12mpractical[39m[38;5;12m [39m[38;5;12mguide[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12mbuilding[39m[38;5;12m [39m[38;5;12mdeep[39m[38;5;12m [39m[38;5;12mlearning[39m[38;5;12m [39m[38;5;12mmodels[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mnew[39m[38;5;12m [39m[38;5;12mfeatures[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mTensorFlow[39m[38;5;12m [39m[38;5;12m2.0[39m[38;5;12m [39m[38;5;12mis[39m[38;5;12m [39m[38;5;12mfilled[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;12mengaging[39m[38;5;12m [39m[38;5;12mprojects,[39m[38;5;12m [39m
[38;5;12msimple[39m[38;5;12m [39m[38;5;12mlanguage,[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mcoverage[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mlatest[39m[38;5;12m [39m[38;5;12malgorithms.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mProbabilistic[0m[38;5;14m[1m [0m[38;5;14m[1mProgramming[0m[38;5;14m[1m [0m[38;5;14m[1mand[0m[38;5;14m[1m [0m[38;5;14m[1mBayesian[0m[38;5;14m[1m [0m[38;5;14m[1mMethods[0m[38;5;14m[1m [0m[38;5;14m[1mfor[0m[38;5;14m[1m [0m[38;5;14m[1mHackers[0m[38;5;12m [39m[38;5;12m(https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mCameron[39m[38;5;12m [39m[38;5;12mDavidson-Pilon.[39m[38;5;12m [39m[38;5;12mIntroduction[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12mBayesian[39m[38;5;12m [39m[38;5;12mmethods[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m
[38;5;12mprobabalistic[39m[38;5;12m [39m[38;5;12mgraphical[39m[38;5;12m [39m[38;5;12mmodels[39m[38;5;12m [39m[38;5;12musing[39m[38;5;12m [39m[38;5;12mtensorflow-probability[39m[38;5;12m [39m[38;5;12m(and,[39m[38;5;12m [39m[38;5;12malternatively[39m[38;5;12m [39m[38;5;12mPyMC2/3).[39m[38;5;12m [39m





[38;2;255;187;0m[4mContributions[0m

[38;5;12mYour contributions are always welcome![39m

[38;5;12mIf you want to contribute to this list (please do), send me a pull request or contact me [39m[38;5;14m[1m@jtoy[0m[38;5;12m (https://twitter.com/jtoy)[39m
[38;5;12mAlso, if you notice that any of the above listed repositories should be deprecated, due to any of the following reasons:[39m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;12mRepository's owner explicitly say that "this library is not maintained".[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;12mNot committed for long time (2~3 years).[39m

[38;5;12mMore info on the [39m[38;5;14m[1mguidelines[0m[38;5;12m (https://github.com/jtoy/awesome-tensorflow/blob/master/contributing.md)[39m




[38;2;255;187;0m[4mCredits[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;12mSome of the python libraries were cut-and-pasted from [39m[38;5;14m[1mvinta[0m[38;5;12m (https://github.com/vinta/awesome-python)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;12mThe few go reference I found where pulled from [39m[38;5;14m[1mthis page[0m[38;5;12m (https://code.google.com/p/go-wiki/wiki/Projects#Machine_Learning)[39m

