rhetenor/awesome-awesomeness
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

update

Browse Source
This commit is contained in:
Jonas Zeunert
2025-07-18 23:13:11 +02:00
parent c9485bf576
commit 652812eed0
2354 changed files with 1266414 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

691
html/tensorflow.md2.html Normal file
View File

@@ -0,0 +1,691 @@
<h1 id="awesome-tensorflow-awesome">Awesome TensorFlow <a
href="https://github.com/jtoy/awesome"><img
src="https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg"
alt="Awesome" /></a></h1>
<p>A curated list of awesome TensorFlow experiments, libraries, and
projects. Inspired by awesome-machine-learning.</p>
<h2 id="what-is-tensorflow">What is TensorFlow?</h2>
<p>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.</p>
<p>More info <a href="http://tensorflow.org">here</a>.</p>
<h2 id="table-of-contents">Table of Contents</h2>
<!-- MarkdownTOC depth=4 -->
<ul>
<li><a href="#github-tutorials">Tutorials</a></li>
<li><a href="#github-projects">Models/Projects</a></li>
<li><a href="#github-powered-by">Powered by TensorFlow</a></li>
<li><a href="#libraries">Libraries</a></li>
<li><a href="#tools-utils">Tools/Utilities</a></li>
<li><a href="#video">Videos</a></li>
<li><a href="#papers">Papers</a></li>
<li><a href="#blogs">Blog posts</a></li>
<li><a href="#community">Community</a></li>
<li><a href="#books">Books</a></li>
</ul>
<!-- /MarkdownTOC -->
<p><a name="github-tutorials" /></p>
<h2 id="tutorials">Tutorials</h2>
<ul>
<li><a href="https://github.com/pkmital/tensorflow_tutorials">TensorFlow
Tutorial 1</a> - From the basics to slightly more interesting
applications of TensorFlow</li>
<li><a href="https://github.com/nlintz/TensorFlow-Tutorials">TensorFlow
Tutorial 2</a> - Introduction to deep learning based on Google’s
TensorFlow framework. These tutorials are direct ports of Newmu’s
Theano</li>
<li><a
href="https://github.com/Hvass-Labs/TensorFlow-Tutorials">TensorFlow
Tutorial 3</a> - These tutorials are intended for beginners in Deep
Learning and TensorFlow with well-documented code and YouTube
videos.</li>
<li><a
href="https://github.com/aymericdamien/TensorFlow-Examples">TensorFlow
Examples</a> - TensorFlow tutorials and code examples for beginners</li>
<li><a href="https://github.com/sjchoi86/Tensorflow-101">Sungjoon’s
TensorFlow-101</a> - TensorFlow tutorials written in Python with Jupyter
Notebook</li>
<li><a href="https://github.com/terryum/TensorFlow_Exercises">Terry Um’s
TensorFlow Exercises</a> - Re-create the codes from other TensorFlow
examples</li>
<li><a
href="https://github.com/samjabrahams/tensorflow-on-raspberry-pi">Installing
TensorFlow on Raspberry Pi 3</a> - TensorFlow compiled and running
properly on the Raspberry Pi</li>
<li><a
href="https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition">Classification
on time series</a> - Recurrent Neural Network classification in
TensorFlow with LSTM on cellphone sensor data</li>
<li><a
href="https://omid.al/posts/2017-02-20-Tutorial-Build-Your-First-Tensorflow-Android-App.html">Getting
Started with TensorFlow on Android</a> - Build your first TensorFlow
Android app</li>
<li><a
href="https://github.com/guillaume-chevalier/seq2seq-signal-prediction">Predict
time series</a> - Learn to use a seq2seq model on simple datasets as an
introduction to the vast array of possibilities that this architecture
offers</li>
<li><a href="https://github.com/Mazecreator/TensorFlow-SIRDS">Single
Image Random Dot Stereograms</a> - 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.</li>
<li><a href="http://web.stanford.edu/class/cs20si/syllabus.html">CS20
SI: TensorFlow for DeepLearning Research</a> - Stanford Course about
Tensorflow from 2017 - <a
href="http://web.stanford.edu/class/cs20si/syllabus.html">Syllabus</a> -
<a
href="https://youtu.be/g-EvyKpZjmQ?list=PLSPPwKHXGS2110rEaNH7amFGmaD5hsObs">Unofficial
Videos</a></li>
<li><a href="https://github.com/astorfi/TensorFlow-World">TensorFlow
World</a> - Concise and ready-to-use TensorFlow tutorials with detailed
documentation are provided.</li>
<li><a href="https://github.com/vahidk/EffectiveTensorflow">Effective
Tensorflow</a> - TensorFlow howtos and best practices. Covers the basics
as well as advanced topics.</li>
<li><a
href="http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html">TensorLayer</a>
- Modular implementation for TensorFlow’s official tutorials. (<a
href="https://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html">CN</a>).</li>
<li><a
href="https://www.lighttag.io/blog/tensorflow-estimator-api/">Understanding
The Tensorflow Estimator API</a> A conceptual overview of the Estimator
API, when you’d use it and why.</li>
<li><a
href="https://www.coursera.org/learn/introduction-tensorflow">Introduction
to TensorFlow for Artificial Intelligence, Machine Learning, and Deep
Learning</a> - Introduction to Tensorflow offered by Coursera</li>
<li><a
href="https://www.coursera.org/learn/convolutional-neural-networks-tensorflow">Convolutional
Neural Networks in TensorFlow</a> - Convolutional Neural Networks in
Tensorflow, offered by Coursera</li>
<li><a
href="https://tensorlayerx.readthedocs.io/en/latest/index.html#user-guide">TensorLayerX</a>
- Using TensorFlow like PyTorch. (<a
href="https://tensorlayerx.readthedocs.io/en/latest/index.html#">Api
docs</a>)</li>
</ul>
<p><a name="github-projects" /></p>
<h2 id="modelsprojects">Models/Projects</h2>
<ul>
<li><a
href="https://github.com/Mrgemy95/Tensorflow-Project-Template">Tensorflow-Project-Template</a>
- A simple and well-designed template for your tensorflow project.</li>
<li><a href="https://github.com/yunjey/dtn-tensorflow">Domain Transfer
Network</a> - Implementation of Unsupervised Cross-Domain Image
Generation</li>
<li><a href="https://github.com/yunjey/show_attend_and_tell">Show,
Attend and Tell</a> - Attention Based Image Caption Generator</li>
<li><a href="https://github.com/cysmith/neural-style-tf">Neural
Style</a> Implementation of Neural Style</li>
<li><a href="https://github.com/tensorlayer/srgan">SRGAN</a> -
Photo-Realistic Single Image Super-Resolution Using a Generative
Adversarial Network</li>
<li><a href="https://github.com/google/prettytensor">Pretty Tensor</a> -
Pretty Tensor provides a high level builder API</li>
<li><a href="https://github.com/anishathalye/neural-style">Neural
Style</a> - An implementation of neural style</li>
<li><a href="https://github.com/denti/AlexNet3D">AlexNet3D</a> - An
implementations of AlexNet3D. Simple AlexNet model but with 3D
convolutional layers (conv3d).</li>
<li><a
href="https://github.com/samjabrahams/tensorflow-white-paper-notes">TensorFlow
White Paper Notes</a> - Annotated notes and summaries of the TensorFlow
white paper, along with SVG figures and links to documentation</li>
<li><a
href="https://github.com/ckmarkoh/neuralart_tensorflow">NeuralArt</a> -
Implementation of A Neural Algorithm of Artistic Style</li>
<li><a
href="https://github.com/hardmaru/write-rnn-tensorflow">Generative
Handwriting Demo using TensorFlow</a> - An attempt to implement the
random handwriting generation portion of Alex Graves’ paper</li>
<li><a href="https://github.com/carpedm20/NTM-tensorflow">Neural Turing
Machine in TensorFlow</a> - implementation of Neural Turing Machine</li>
<li><a href="https://github.com/agermanidis/thingscoop">GoogleNet
Convolutional Neural Network Groups Movie Scenes By Setting</a> -
Search, filter, and describe videos based on objects, places, and other
things that appear in them</li>
<li><a
href="https://github.com/tokestermw/tensorflow-shakespeare">Neural
machine translation between the writings of Shakespeare and modern
English using TensorFlow</a> - This performs a monolingual translation,
going from modern English to Shakespeare and vice-versa.</li>
<li><a href="https://github.com/Conchylicultor/DeepQA">Chatbot</a> -
Implementation of <a href="http://arxiv.org/abs/1506.05869">“A neural
conversational model”</a></li>
<li><a
href="https://github.com/tensorlayer/seq2seq-chatbot">Seq2seq-Chatbot</a>
- Chatbot in 200 lines of code</li>
<li><a href="https://github.com/tensorlayer/dcgan">DCGAN</a> - Deep
Convolutional Generative Adversarial Networks</li>
<li><a href="https://github.com/zsdonghao/text-to-image">GAN-CLS</a>
-Generative Adversarial Text to Image Synthesis</li>
<li><a href="https://github.com/zsdonghao/Unsup-Im2Im">im2im</a> -
Unsupervised Image to Image Translation with Generative Adversarial
Networks</li>
<li><a href="https://github.com/luoxier/CycleGAN_Tensorlayer">Improved
CycleGAN</a> - Unpaired Image to Image Translation</li>
<li><a href="https://github.com/nebulaV/DAGAN">DAGAN</a> - Fast
Compressed Sensing MRI Reconstruction</li>
<li><a href="https://github.com/pavelgonchar/colornet">Colornet - Neural
Network to colorize grayscale images</a> - Neural Network to colorize
grayscale images</li>
<li><a
href="https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow">Neural
Caption Generator</a> - Implementation of <a
href="http://arxiv.org/abs/1411.4555">“Show and Tell”</a></li>
<li><a
href="https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow">Neural
Caption Generator with Attention</a> - Implementation of <a
href="http://arxiv.org/abs/1502.03044">“Show, Attend and Tell”</a></li>
<li><a
href="https://github.com/jazzsaxmafia/Weakly_detector">Weakly_detector</a>
- Implementation of <a
href="http://cnnlocalization.csail.mit.edu/">“Learning Deep Features for
Discriminative Localization”</a></li>
<li><a href="https://github.com/jazzsaxmafia/dcn.tf">Dynamic Capacity
Networks</a> - Implementation of <a
href="http://arxiv.org/abs/1511.07838">“Dynamic Capacity
Networks”</a></li>
<li><a href="https://github.com/dwiel/tensorflow_hmm">HMM in
TensorFlow</a> - Implementation of viterbi and forward/backward
algorithms for HMM</li>
<li><a href="https://github.com/trailbehind/DeepOSM">DeepOSM</a> - Train
TensorFlow neural nets with OpenStreetMap features and satellite
imagery.</li>
<li><a
href="https://github.com/devsisters/DQN-tensorflow">DQN-tensorflow</a> -
TensorFlow implementation of DeepMind’s ‘Human-Level Control through
Deep Reinforcement Learning’ with OpenAI Gym by Devsisters.com</li>
<li><a
href="https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_atari_pong.py">Policy
Gradient</a> - For Playing Atari Ping Pong</li>
<li><a
href="https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_frozenlake_dqn.py">Deep
Q-Network</a> - For Playing Frozen Lake Game</li>
<li><a
href="https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_cartpole_ac.py">AC</a>
- Actor Critic for Playing Discrete Action space Game (Cartpole)</li>
<li><a
href="https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_bipedalwalker_a3c_continuous_action.py">A3C</a>
- Asynchronous Advantage Actor Critic (A3C) for Continuous Action Space
(Bipedal Walker)</li>
<li><a
href="https://github.com/zsdonghao/Imitation-Learning-Dagger-Torcs">DAGGER</a>
- For Playing <a href="https://github.com/ugo-nama-kun/gym_torcs">Gym
Torcs</a></li>
<li><a href="https://github.com/jjkke88/RL_toolbox">TRPO</a> - For
Continuous and Discrete Action Space by</li>
<li><a href="https://github.com/fomorians/highway-cnn">Highway
Network</a> - TensorFlow implementation of <a
href="http://arxiv.org/abs/1507.06228">“Training Very Deep Networks”</a>
with a <a
href="https://medium.com/jim-fleming/highway-networks-with-tensorflow-1e6dfa667daa#.ndicn1i27">blog
post</a></li>
<li><a
href="https://github.com/tqtg/hierarchical-attention-networks">Hierarchical
Attention Networks</a> - TensorFlow implementation of <a
href="https://www.cs.cmu.edu/~hovy/papers/16HLT-hierarchical-attention-networks.pdf">“Hierarchical
Attention Networks for Document Classification”</a></li>
<li><a
href="https://github.com/dennybritz/cnn-text-classification-tf">Sentence
Classification with CNN</a> - TensorFlow implementation of <a
href="http://arxiv.org/abs/1408.5882">“Convolutional Neural Networks for
Sentence Classification”</a> with a <a
href="http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/">blog
post</a></li>
<li><a href="https://github.com/domluna/memn2n">End-To-End Memory
Networks</a> - Implementation of <a
href="http://arxiv.org/abs/1503.08895">End-To-End Memory
Networks</a></li>
<li><a
href="https://github.com/carpedm20/lstm-char-cnn-tensorflow">Character-Aware
Neural Language Models</a> - TensorFlow implementation of <a
href="http://arxiv.org/abs/1508.06615">Character-Aware Neural Language
Models</a></li>
<li><a href="https://github.com/thtrieu/yolotf">YOLO TensorFlow ++</a> -
TensorFlow implementation of ‘YOLO: Real-Time Object Detection’, with
training and an actual support for real-time running on mobile
devices.</li>
<li><a href="https://github.com/ibab/tensorflow-wavenet">Wavenet</a> -
This is a TensorFlow implementation of the <a
href="https://deepmind.com/blog/wavenet-generative-model-raw-audio/">WaveNet
generative neural network architecture</a> for audio generation.</li>
<li><a href="https://github.com/trigeorgis/mdm">Mnemonic Descent
Method</a> - Tensorflow implementation of <a
href="http://ibug.doc.ic.ac.uk/media/uploads/documents/trigeorgis2016mnemonic.pdf">“Mnemonic
Descent Method: A recurrent process applied for end-to-end face
alignment”</a></li>
<li><a href="https://github.com/InFoCusp/tf_cnnvis">CNN visualization
using Tensorflow</a> - Tensorflow implementation of <a
href="https://www.cs.nyu.edu/~fergus/papers/zeilerECCV2014.pdf">“Visualizing
and Understanding Convolutional Networks”</a></li>
<li><a href="https://github.com/Singularity42/VGAN-Tensorflow">VGAN
Tensorflow</a> - Tensorflow implementation for MIT <a
href="http://carlvondrick.com/tinyvideo/">“Generating Videos with Scene
Dynamics”</a> by Vondrick et al.</li>
<li><a
href="https://github.com/astorfi/3D-convolutional-speaker-recognition">3D
Convolutional Neural Networks in TensorFlow</a> - Implementation of <a
href="https://arxiv.org/abs/1705.09422">“3D Convolutional Neural
Networks for Speaker Verification application”</a> in TensorFlow by
Torfi et al.</li>
<li><a href="https://github.com/zsdonghao/u-net-brain-tumor">U-Net</a> -
For Brain Tumor Segmentation</li>
<li><a
href="https://github.com/zsdonghao/Spatial-Transformer-Nets">Spatial
Transformer Networks</a> - Learn the Transformation Function</li>
<li><a href="https://github.com/astorfi/lip-reading-deeplearning">Lip
Reading - Cross Audio-Visual Recognition using 3D Architectures in
TensorFlow</a> - TensorFlow Implementation of <a
href="https://arxiv.org/abs/1706.05739">“Cross Audio-Visual Recognition
in the Wild Using Deep Learning”</a> by Torfi et al.</li>
<li><a href="https://github.com/akosiorek/hart">Attentive Object
Tracking</a> - Implementation of <a
href="https://arxiv.org/abs/1706.09262">“Hierarchical Attentive
Recurrent Tracking”</a></li>
<li><a href="https://github.com/laxatives/TensorFlow-TransX">Holographic
Embeddings for Graph Completion and Link Prediction</a> - Implementation
of <a href="http://arxiv.org/abs/1510.04935">Holographic Embeddings of
Knowledge Graphs</a></li>
<li><a
href="https://github.com/akosiorek/attend_infer_repeat">Unsupervised
Object Counting</a> - Implementation of <a
href="https://papers.nips.cc/paper/6230-attend-infer-repeat-fast-scene-understanding-with-generative-models">“Attend,
Infer, Repeat”</a></li>
<li><a href="https://github.com/apcode/tensorflow_fasttext">Tensorflow
FastText</a> - A simple embedding based text classifier inspired by
Facebook’s fastText.</li>
<li><a
href="https://github.com/mlachmish/MusicGenreClassification">MusicGenreClassification</a>
- Classify music genre from a 10 second sound stream using a Neural
Network.</li>
<li><a href="https://github.com/kubeflow/kubeflow">Kubeflow</a> -
Framework for easily using Tensorflow with Kubernetes.</li>
<li><a href="https://github.com/taehoonlee/tensornets">TensorNets</a> -
40+ Popular Computer Vision Models With Pre-trained Weights.</li>
<li><a href="https://github.com/divamgupta/ladder_network_keras">Ladder
Network</a> - Implementation of Ladder Network for Semi-Supervised
Learning in Keras and Tensorflow</li>
<li><a href="https://github.com/juniorxsound/TF-Unet">TF-Unet</a> -
General purpose U-Network implemented in Keras for image
segmentation</li>
<li><a href="https://github.com/sarus-tech/tf2-published-models">Sarus
TF2 Models</a> - A long list of recent generative models implemented in
clean, easy to reuse, Tensorflow 2 code (Plain Autoencoder, VAE, VQ-VAE,
PixelCNN, Gated PixelCNN, PixelCNN++, PixelSNAIL, Conditional Neural
Processes).</li>
<li><a href="https://www.tensorflow.org/lite/guide/model_maker">Model
Maker</a> - A transfer learning library that simplifies the process of
training, evaluation and deployment for TensorFlow Lite models (support:
Image Classification, Object Detection, Text Classification, BERT
Question Answer, Audio Classification, Recommendation etc.; <a
href="https://www.tensorflow.org/lite/api_docs/python/tflite_model_maker">API
reference</a>).</li>
</ul>
<p><a name="github-powered-by" /></p>
<h2 id="powered-by-tensorflow">Powered by TensorFlow</h2>
<ul>
<li><a href="https://github.com/gliese581gg/YOLO_tensorflow">YOLO
TensorFlow</a> - Implementation of ‘YOLO : Real-Time Object
Detection’</li>
<li><a
href="https://github.com/natanielruiz/android-yolo">android-yolo</a> -
Real-time object detection on Android using the YOLO network, powered by
TensorFlow.</li>
<li><a href="https://github.com/tensorflow/magenta">Magenta</a> -
Research project to advance the state of the art in machine intelligence
for music and art generation</li>
</ul>
<p><a name="libraries" /></p>
<h2 id="libraries">Libraries</h2>
<ul>
<li><a href="https://www.tensorflow.org/guide/estimators">TensorFlow
Estimators</a> - high-level TensorFlow API that greatly simplifies
machine learning programming (originally <a
href="https://github.com/tensorflow/skflow">tensorflow/skflow</a>)</li>
<li><a href="https://tensorflow.rstudio.com/">R Interface to
TensorFlow</a> - R interface to TensorFlow APIs, including Estimators,
Keras, Datasets, etc.</li>
<li><a href="https://github.com/tensorflow/lattice">Lattice</a> -
Implementation of Monotonic Calibrated Interpolated Look-Up Tables in
TensorFlow</li>
<li><a
href="https://github.com/somaticio/tensorflow.rb">tensorflow.rb</a> -
TensorFlow native interface for ruby using SWIG</li>
<li><a href="https://github.com/tflearn/tflearn">tflearn</a> - Deep
learning library featuring a higher-level API</li>
<li><a href="https://github.com/tensorlayer/tensorlayer">TensorLayer</a>
- Deep learning and reinforcement learning library for researchers and
engineers</li>
<li><a
href="https://github.com/tensorflow/models/tree/master/inception/inception/slim">TensorFlow-Slim</a>
- High-level library for defining models</li>
<li><a href="https://github.com/tjhunter/tensorframes">TensorFrames</a>
- TensorFlow binding for Apache Spark</li>
<li><a href="https://github.com/reinforceio/tensorforce">TensorForce</a>
- TensorForce: A TensorFlow library for applied reinforcement
learning</li>
<li><a
href="https://github.com/yahoo/TensorFlowOnSpark">TensorFlowOnSpark</a>
- initiative from Yahoo! to enable distributed TensorFlow with Apache
Spark.</li>
<li><a
href="https://github.com/ethereon/caffe-tensorflow">caffe-tensorflow</a>
- Convert Caffe models to TensorFlow format</li>
<li><a href="http://keras.io">keras</a> - Minimal, modular deep learning
library for TensorFlow and Theano</li>
<li><a
href="https://github.com/tensorflow/models/tree/master/syntaxnet">SyntaxNet:
Neural Models of Syntax</a> - A TensorFlow implementation of the models
described in <a href="http://arxiv.org/pdf/1603.06042.pdf">Globally
Normalized Transition-Based Neural Networks, Andor et
al. (2016)</a></li>
<li><a href="https://github.com/transcranial/keras-js">keras-js</a> -
Run Keras models (tensorflow backend) in the browser, with GPU
support</li>
<li><a href="https://github.com/welschma/NNFlow">NNFlow</a> - Simple
framework allowing to read-in ROOT NTuples by converting them to a Numpy
array and then use them in Google Tensorflow.</li>
<li><a href="https://github.com/deepmind/sonnet">Sonnet</a> - Sonnet is
DeepMind’s library built on top of TensorFlow for building complex
neural networks.</li>
<li><a href="https://github.com/ppwwyyxx/tensorpack">tensorpack</a> -
Neural Network Toolbox on TensorFlow focusing on training speed and on
large datasets.</li>
<li><a
href="https://github.com/mortendahl/tf-encrypted">tf-encrypted</a> -
Layer on top of TensorFlow for doing machine learning on encrypted
data</li>
<li><a
href="https://github.com/nerox8664/pytorch2keras">pytorch2keras</a> -
Convert PyTorch models to Keras (with TensorFlow backend) format</li>
<li><a href="https://github.com/stjordanis/gluon2keras">gluon2keras</a>
- Convert Gluon models to Keras (with TensorFlow backend) format</li>
<li><a href="https://doc-ai.github.io/tensorio/">TensorIO</a> -
Lightweight, cross-platform library for deploying TensorFlow Lite models
to mobile devices.</li>
<li><a
href="https://github.com/stellargraph/stellargraph">StellarGraph</a> -
Machine Learning on Graphs, a Python library for machine learning on
graph-structured (network-structured) data.</li>
<li><a href="https://github.com/ElPapi42/DeepBay">DeepBay</a> -
High-Level Keras Complement for implement common architectures stacks,
served as easy to use plug-n-play modules</li>
<li><a
href="https://www.tensorflow.org/probability">Tensorflow-Probability</a>
- Probabilistic programming built on TensorFlow that makes it easy to
combine probabilistic models and deep learning on modern hardware.</li>
<li><a
href="https://github.com/tensorlayer/TensorLayerX">TensorLayerX</a> -
TensorLayerX: A Unified Deep Learning Framework for All Hardwares,
Backends and OS, including TensorFlow.</li>
<li><a href="https://github.com/rdabra/txeo">Txeo</a> - A modern C++
wrapper for TensorFlow.</li>
</ul>
<p><a name="tools-utils" /></p>
<h2 id="toolsutilities">Tools/Utilities</h2>
<ul>
<li><a
href="https://github.com/nebuly-ai/nebullvm/tree/main/apps/accelerate/speedster">Speedster</a>
- Automatically apply SOTA optimization techniques to achieve the
maximum inference speed-up on your hardware.</li>
<li><a href="https://guild.ai">Guild AI</a> - Task runner and package
manager for TensorFlow</li>
<li><a href="https://github.com/ml-tooling/ml-workspace">ML
Workspace</a> - 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.</li>
<li><a
href="https://github.com/radi-cho/create-tf-app">create-tf-app</a> -
Project builder command line tool for Tensorflow covering environment
management, linting, and logging.</li>
</ul>
<p><a name="video" /></p>
<h2 id="videos">Videos</h2>
<ul>
<li><a href="http://bit.ly/1OX8s8Y">TensorFlow Guide 1</a> - A guide to
installation and use</li>
<li><a href="http://bit.ly/1R27Ki9">TensorFlow Guide 2</a> -
Continuation of first video</li>
<li><a href="http://bit.ly/1TCNmEY">TensorFlow Basic Usage</a> - A guide
going over basic usage</li>
<li><a href="http://bit.ly/1L9IfJx">TensorFlow Deep MNIST for
Experts</a> - Goes over Deep MNIST</li>
<li><a href="https://www.youtube.com/watch?v=ReaxoSIM5XQ">TensorFlow
Udacity Deep Learning</a> - Basic steps to install TensorFlow for free
on the Cloud 9 online service with 1Gb of data</li>
<li><a
href="http://video.foxnews.com/v/4611174773001/why-google-wants-everyone-to-have-access-to-tensorflow/?#sp=show-clips">Why
Google wants everyone to have access to TensorFlow</a></li>
<li><a
href="http://blog.altoros.com/videos-from-tensorflow-silicon-valley-meetup-january-19-2016.html">Videos
from TensorFlow Silicon Valley Meet Up 1/19/2016</a></li>
<li><a
href="http://blog.altoros.com/videos-from-tensorflow-seattle-meetup-jan-21-2016.html">Videos
from TensorFlow Silicon Valley Meet Up 1/21/2016</a></li>
<li><a
href="https://www.youtube.com/watch?v=L8Y2_Cq2X5s&amp;index=7&amp;list=PLmImxx8Char9Ig0ZHSyTqGsdhb9weEGam">Stanford
CS224d Lecture 7 - Introduction to TensorFlow, 19th Apr 2016</a> -
CS224d Deep Learning for Natural Language Processing by Richard
Socher</li>
<li><a
href="https://youtu.be/GZBIPwdGtkk?list=PLBkISg6QfSX9HL6us70IBs9slFciFFa4W">Diving
into Machine Learning through TensorFlow</a> - Pycon 2016 Portland
Oregon, <a
href="https://storage.googleapis.com/amy-jo/talks/tf-workshop.pdf">Slide</a>
&amp; <a href="https://github.com/amygdala/tensorflow-workshop">Code</a>
by Julia Ferraioli, Amy Unruh, Eli Bixby</li>
<li><a href="https://youtu.be/XYwIDn00PAo">Large Scale Deep Learning
with TensorFlow</a> - Spark Summit 2016 Keynote by Jeff Dean</li>
<li><a href="https://www.youtube.com/watch?v=vq2nnJ4g6N0">Tensorflow and
deep learning - without at PhD</a> - by Martin Görner</li>
<li><a href="https://www.youtube.com/watch?v=fTUwdXUFfI8">Tensorflow and
deep learning - without at PhD, Part 2 (Google Cloud Next ’17)</a> - by
Martin Görner</li>
<li><a href="https://youtu.be/P8MZ1Z2LHrw">Image recognition in Go using
TensorFlow</a> - by Alex Pliutau</li>
</ul>
<p><a name="papers" /></p>
<h2 id="papers">Papers</h2>
<ul>
<li><a
href="http://download.tensorflow.org/paper/whitepaper2015.pdf">TensorFlow:
Large-Scale Machine Learning on Heterogeneous Distributed Systems</a> -
This paper describes the TensorFlow interface and an implementation of
that interface that we have built at Google</li>
<li><a href="https://arxiv.org/pdf/1708.02637.pdf">TensorFlow
Estimators: Managing Simplicity vs. Flexibility in High-Level Machine
Learning Frameworks</a></li>
<li><a href="https://arxiv.org/abs/1612.04251">TF.Learn: TensorFlow’s
High-level Module for Distributed Machine Learning</a></li>
<li><a href="http://arxiv.org/abs/1511.06435">Comparative Study of Deep
Learning Software Frameworks</a> - 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</li>
<li><a href="http://arxiv.org/abs/1603.02339">Distributed TensorFlow
with MPI</a> - In this paper, we extend recently proposed Google
TensorFlow for execution on large scale clusters using Message Passing
Interface (MPI)</li>
<li><a href="http://arxiv.org/abs/1603.06042">Globally Normalized
Transition-Based Neural Networks</a> - This paper describes the models
behind <a
href="https://github.com/tensorflow/models/tree/master/syntaxnet">SyntaxNet</a>.</li>
<li><a href="https://arxiv.org/abs/1605.08695">TensorFlow: A system for
large-scale machine learning</a> - This paper describes the TensorFlow
dataflow model in contrast to existing systems and demonstrate the
compelling performance</li>
<li><a href="https://arxiv.org/abs/1707.08551">TensorLayer: A Versatile
Library for Efficient Deep Learning Development</a> - This paper
describes a versatile Python library that aims at helping researchers
and engineers efficiently develop deep learning systems. (Winner of The
Best Open Source Software Award of ACM MM 2017)</li>
</ul>
<p><a name="blogs" /></p>
<h2 id="official-announcements">Official announcements</h2>
<ul>
<li><a
href="https://googleblog.blogspot.com/2015/11/tensorflow-smarter-machine-learning-for.html">TensorFlow:
smarter machine learning, for everyone</a> - An introduction to
TensorFlow</li>
<li><a
href="http://googleresearch.blogspot.com/2016/05/announcing-syntaxnet-worlds-most.html">Announcing
SyntaxNet: The World’s Most Accurate Parser Goes Open Source</a> -
Release of SyntaxNet, “an open-source neural network framework
implemented in TensorFlow that provides a foundation for Natural
Language Understanding systems.</li>
</ul>
<h2 id="blog-posts">Blog posts</h2>
<ul>
<li><a href="http://blog.tensorflow.org/">Official Tensorflow
Blog</a></li>
<li><a href="https://archive.fo/o9asj">Why TensorFlow will change the
Game for AI</a></li>
<li><a
href="http://petewarden.com/2016/02/28/tensorflow-for-poets">TensorFlow
for Poets</a> - Goes over the implementation of TensorFlow</li>
<li><a
href="http://terrytangyuan.github.io/2016/03/14/scikit-flow-intro/">Introduction
to Scikit Flow - Simplified Interface to TensorFlow</a> - Key Features
Illustrated</li>
<li><a
href="http://terrytangyuan.github.io/2016/07/08/understand-and-build-tensorflow-estimator/">Building
Machine Learning Estimator in TensorFlow</a> - Understanding the
Internals of TensorFlow Learn Estimators</li>
<li><a
href="http://terrytangyuan.github.io/2016/08/06/tensorflow-not-just-deep-learning/">TensorFlow
- Not Just For Deep Learning</a></li>
<li><a href="https://indico.io/blog/indico-tensorflow">The indico
Machine Learning Team’s take on TensorFlow</a></li>
<li><a
href="https://indico.io/blog/the-good-bad-ugly-of-tensorflow/">The Good,
Bad, &amp; Ugly of TensorFlow</a> - A survey of six months rapid
evolution (+ tips/hacks and code to fix the ugly stuff), Dan Kuster at
Indico, May 9, 2016</li>
<li><a
href="http://joelgrus.com/2016/05/23/fizz-buzz-in-tensorflow/">Fizz Buzz
in TensorFlow</a> - A joke by Joel Grus</li>
<li><a
href="http://www.wildml.com/2016/08/rnns-in-tensorflow-a-practical-guide-and-undocumented-features/">RNNs
In TensorFlow, A Practical Guide And Undocumented Features</a> -
Step-by-step guide with full code examples on GitHub.</li>
<li><a
href="http://maxmelnick.com/2016/07/04/visualizing-tensorflow-retrain.html">Using
TensorBoard to Visualize Image Classification Retraining in
TensorFlow</a></li>
<li><a
href="http://warmspringwinds.github.io/tensorflow/tf-slim/2016/12/21/tfrecords-guide/">TFRecords
Guide</a> semantic segmentation and handling the TFRecord file
format.</li>
<li><a
href="https://blog.mindorks.com/android-tensorflow-machine-learning-example-ff0e9b2654cc">TensorFlow
Android Guide</a> - Android TensorFlow Machine Learning Example.</li>
<li><a
href="https://software.intel.com/en-us/articles/tensorflow-optimizations-on-modern-intel-architecture">TensorFlow
Optimizations on Modern Intel® Architecture</a> - Introduces TensorFlow
optimizations on Intel® Xeon® and Intel® Xeon Phi™ processor-based
platforms based on an Intel/Google collaboration.</li>
<li><a
href="https://developers.googleblog.com/2017/09/how-machine-learning-with-tensorflow.html">Coca-Cola’s
Image Recognition App</a> Coca-Cola’s product code image recognizing
neural network with user input feedback loop.</li>
<li><a
href="https://www.letslearnai.com/2018/02/02/how-does-the-machine-learning-library-tensorflow-work.html">How
Does The TensorFlow Work</a> How Does The Machine Learning Library
TensorFlow Work?</li>
</ul>
<p><a name="community" /></p>
<h2 id="community">Community</h2>
<ul>
<li><a href="http://stackoverflow.com/questions/tagged/tensorflow">Stack
Overflow</a></li>
<li><a href="https://twitter.com/tensorflow"><span class="citation"
data-cites="TensorFlow">@TensorFlow</span> on Twitter</a></li>
<li><a href="https://www.reddit.com/r/tensorflow">Reddit</a></li>
<li><a
href="https://groups.google.com/a/tensorflow.org/forum/#!forum/discuss">Mailing
List</a></li>
</ul>
<p><a name="books" /></p>
<h2 id="books">Books</h2>
<ul>
<li><a href="http://tensorflowbook.com">Machine Learning with
TensorFlow</a> 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.</li>
<li><a
href="http://www.jorditorres.org/first-contact-with-tensorflow/">First
Contact with TensorFlow</a> by Jordi Torres, professor at UPC Barcelona
Tech and a research manager and senior advisor at Barcelona
Supercomputing Center</li>
<li><a
href="https://machinelearningmastery.com/deep-learning-with-python/">Deep
Learning with Python</a> - Develop Deep Learning Models on Theano and
TensorFlow Using Keras by Jason Brownlee</li>
<li><a
href="https://bleedingedgepress.com/tensor-flow-for-machine-intelligence/">TensorFlow
for Machine Intelligence</a> - Complete guide to use TensorFlow from the
basics of graph computing, to deep learning models to using it in
production environments - Bleeding Edge Press</li>
<li><a
href="https://www.packtpub.com/big-data-and-business-intelligence/getting-started-tensorflow">Getting
Started with TensorFlow</a> - Get up and running with the latest
numerical computing library by Google and dive deeper into your data, by
Giancarlo Zaccone</li>
<li><a href="http://shop.oreilly.com/product/0636920052289.do">Hands-On
Machine Learning with Scikit-Learn and TensorFlow</a> – by Aurélien
Geron, former lead of the YouTube video classification team. Covers ML
fundamentals, training and deploying deep nets across multiple servers
and GPUs using TensorFlow, the latest CNN, RNN and Autoencoder
architectures, and Reinforcement Learning (Deep Q).</li>
<li><a
href="https://www.packtpub.com/big-data-and-business-intelligence/building-machine-learning-projects-tensorflow">Building
Machine Learning Projects with Tensorflow</a> – by Rodolfo Bonnin. This
book covers various projects in TensorFlow that expose what can be done
with TensorFlow in different scenarios. The book provides projects on
training models, machine learning, deep learning, and working with
various neural networks. Each project is an engaging and insightful
exercise that will teach you how to use TensorFlow and show you how
layers of data can be explored by working with Tensors.</li>
<li><a href="http://www.broadview.com.cn/book/5059">Deep Learning using
TensorLayer</a> - by Hao Dong et al. This book covers both deep learning
and the implementation by using TensorFlow and TensorLayer.</li>
<li><a
href="https://www.manning.com/books/tensorflow-in-action">TensorFlow 2.0
in Action</a> - by Thushan Ganegedara. This practical guide to building
deep learning models with the new features of TensorFlow 2.0 is filled
with engaging projects, simple language, and coverage of the latest
algorithms.</li>
<li><a
href="https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers">Probabilistic
Programming and Bayesian Methods for Hackers</a> - by Cameron
Davidson-Pilon. Introduction to Bayesian methods and probabilistic
graphical models using tensorflow-probability (and, alternatively
PyMC2/3).</li>
</ul>
<p><a name="contributions" /></p>
<h2 id="contributions">Contributions</h2>
<p>Your contributions are always welcome!</p>
<p>If you want to contribute to this list (please do), send me a pull
request or contact me <a href="https://twitter.com/jtoy"><span
class="citation" data-cites="jtoy">@jtoy</span></a> Also, if you notice
that any of the above listed repositories should be deprecated, due to
any of the following reasons:</p>
<ul>
<li>Repository’s owner explicitly say that “this library is not
maintained”.</li>
<li>Not committed for long time (2~3 years).</li>
</ul>
<p>More info on the <a
href="https://github.com/jtoy/awesome-tensorflow/blob/master/contributing.md">guidelines</a></p>
<p><a name="credits" /></p>
<h2 id="credits">Credits</h2>
<ul>
<li>Some of the python libraries were cut-and-pasted from <a
href="https://github.com/vinta/awesome-python">vinta</a></li>
<li>The few go reference I found where pulled from <a
href="https://code.google.com/p/go-wiki/wiki/Projects#Machine_Learning">this
page</a></li>
</ul>
<p><a href="https://github.com/jtoy/awesome-tensorflow">tensorflow.md
Github</a></p>