Blog posts

• Official Tensorflow Blog
• Why TensorFlow will change the Game for AI
• TensorFlow for Poets - Goes over the implementation of TensorFlow
• Introduction to Scikit Flow - Simplified Interface to TensorFlow - Key Features Illustrated
• Building Machine Learning Estimator in TensorFlow - Understanding the Internals of TensorFlow Learn Estimators
• TensorFlow - Not Just For Deep Learning
• The indico Machine Learning Team's take on TensorFlow
• 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
• Fizz Buzz in TensorFlow - A joke by Joel Grus
• Using TensorBoard to Visualize Image Classification Retraining in TensorFlow
• TFRecords Guide
• TensorFlow Android Guide - Android TensorFlow Machine Learning Example.
• TensorFlow Optimizations on Modern Intel® Architecture - Introduces TensorFlow optimizations on Intel® Xeon® and Intel® Xeon Phi™ processor-based platforms based on an Intel/Google collaboration.
• Coca-Cola's Image Recognition App - Cola's product code image recognizing neural network with user input feedback loop.
• How Does The TensorFlow Work
• How Does The TensorFlow Work
• How Does The TensorFlow Work
• The indico Machine Learning Team's take on TensorFlow
• TFRecords Guide
• How Does The TensorFlow Work
• Coca-Cola's Image Recognition App - Cola's product code image recognizing neural network with user input feedback loop.

Books

• Machine Learning with TensorFlow - heavy topic of ML approachable and practicle to a newcomer.
• First Contact with TensorFlow
• Deep Learning with Python - Develop Deep Learning Models on Theano and TensorFlow Using Keras by Jason Brownlee
• TensorFlow 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
• Getting Started with TensorFlow - Get up and running with the latest numerical computing library by Google and dive deeper into your data, by Giancarlo Zaccone
• Hands-On Machine Learning with Scikit-Learn and TensorFlow
• Building Machine Learning Projects with Tensorflow
• Deep Learning using TensorLayer - by Hao Dong et al. This book covers both deep learning and the implmentation by using TensorFlow and TensorLayer.
• TensorFlow 2.0 in Action - 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.
• Machine Learning with TensorFlow - heavy topic of ML approachable and practicle to a newcomer.
• Deep Learning using TensorLayer - by Hao Dong et al. This book covers both deep learning and the implementation by using TensorFlow and TensorLayer.
• Probabilistic Programming and Bayesian Methods for Hackers - by Cameron Davidson-Pilon. Introduction to Bayesian methods and probabilistic graphical models using tensorflow-probability (and, alternatively PyMC2/3).
• Hands-On Machine Learning with Scikit-Learn and TensorFlow
• Getting Started with TensorFlow - Get up and running with the latest numerical computing library by Google and dive deeper into your data, by Giancarlo Zaccone
• Building Machine Learning Projects with Tensorflow
• TensorFlow 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

Community

• Stack Overflow
• @TensorFlow on Twitter
• Reddit
• Mailing List
• Stack Overflow

Contributions

• @jtoy
• @jtoy

Credits

• vinta
• this page

Libraries

• TensorFlow Estimators - high-level TensorFlow API that greatly simplifies machine learning programming (originally tensorflow/skflow)
• R Interface to TensorFlow - R interface to TensorFlow APIs, including Estimators, Keras, Datasets, etc.
• TensorFlow-Slim - High-level library for defining models
• SyntaxNet: Neural Models of Syntax - A TensorFlow implementation of the models described in Globally Normalized Transition-Based Neural Networks, Andor et al. (2016)
• Tensorflow-Probability - Probabilistic programming built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware.
• TensorLayer - Deep learning and reinforcement learning library for researchers and engineers
• Lattice - Implementation of Monotonic Calibrated Interpolated Look-Up Tables in TensorFlow
• tensorflow.rb - TensorFlow native interface for ruby using SWIG
• tflearn - Deep learning library featuring a higher-level API
• TensorFlowOnSpark - initiative from Yahoo! to enable distributed TensorFlow with Apache Spark.
• caffe-tensorflow - Convert Caffe models to TensorFlow format
• keras-js - Run Keras models (tensorflow backend) in the browser, with GPU support
• NNFlow - Simple framework allowing to read-in ROOT NTuples by converting them to a Numpy array and then use them in Google Tensorflow.
• tf-encrypted - Layer on top of TensorFlow for doing machine learning on encrypted data
• gluon2keras - Convert Gluon models to Keras (with TensorFlow backend) format
• TensorIO - Lightweight, cross-platform library for deploying TensorFlow Lite models to mobile devices.
• StellarGraph - Machine Learning on Graphs, a Python library for machine learning on graph-structured (network-structured) data.
• DeepBay - High-Level Keras Complement for implement common architectures stacks, served as easy to use plug-n-play modules
• TensorLayerX - TensorLayerX: A Unified Deep Learning Framework for All Hardwares, Backends and OS, including TensorFlow.
• Txeo - A modern C++ wrapper for TensorFlow.
• TensorForce - TensorForce: A TensorFlow library for applied reinforcement learning
• Sonnet - Sonnet is DeepMind's library built on top of TensorFlow for building complex neural networks.
• tensorpack - Neural Network Toolbox on TensorFlow focusing on training speed and on large datasets.
• TensorFrames - TensorFlow binding for Apache Spark

Models/Projects

• Policy Gradient - For Playing Atari Ping Pong
• Deep Q-Network - For Playing Frozen Lake Game
• AC - Actor Critic for Playing Discrete Action space Game (Cartpole)
• A3C - Asynchronous Advantage Actor Critic (A3C) for Continuous Action Space (Bipedal Walker)
• Tensorflow-Project-Template - A simple and well-designed template for your tensorflow project.
• Neural Style
• SRGAN - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
• Pretty Tensor - Pretty Tensor provides a high level builder API
• Neural Style - An implementation of neural style
• AlexNet3D - An implementations of AlexNet3D. Simple AlexNet model but with 3D convolutional layers (conv3d).
• TensorFlow White Paper Notes - Annotated notes and summaries of the TensorFlow white paper, along with SVG figures and links to documentation
• NeuralArt - Implementation of A Neural Algorithm of Artistic Style
• Generative Handwriting Demo using TensorFlow - An attempt to implement the random handwriting generation portion of Alex Graves' paper
• Neural Turing Machine in TensorFlow - implementation of Neural Turing Machine
• GoogleNet Convolutional Neural Network Groups Movie Scenes By Setting - Search, filter, and describe videos based on objects, places, and other things that appear in them
• Neural machine translation between the writings of Shakespeare and modern English using TensorFlow - This performs a monolingual translation, going from modern English to Shakespeare and vice-versa.
• Chatbot - Implementation of "A neural conversational model"
• Seq2seq-Chatbot - Chatbot in 200 lines of code
• DCGAN - Deep Convolutional Generative Adversarial Networks
• GAN-CLS - Generative Adversarial Text to Image Synthesis
• im2im - Unsupervised Image to Image Translation with Generative Adversarial Networks
• Improved CycleGAN - Unpaired Image to Image Translation
• Colornet - Neural Network to colorize grayscale images - Neural Network to colorize grayscale images
• Neural Caption Generator with Attention - Implementation of "Show, Attend and Tell"
• Weakly_detector - Implementation of "Learning Deep Features for Discriminative Localization"
• Dynamic Capacity Networks - Implementation of "Dynamic Capacity Networks"
• HMM in TensorFlow - Implementation of viterbi and forward/backward algorithms for HMM
• DeepOSM - Train TensorFlow neural nets with OpenStreetMap features and satellite imagery.
• DQN-tensorflow - TensorFlow implementation of DeepMind's 'Human-Level Control through Deep Reinforcement Learning' with OpenAI Gym by Devsisters.com
• DAGGER - For Playing Gym Torcs
• TRPO - For Continuous and Discrete Action Space by
• Highway Network - TensorFlow implementation of "Training Very Deep Networks" with a blog post
• Hierarchical Attention Networks - TensorFlow implementation of "Hierarchical Attention Networks for Document Classification"
• Sentence Classification with CNN - TensorFlow implementation of "Convolutional Neural Networks for Sentence Classification" with a blog post
• End-To-End Memory Networks - Implementation of End-To-End Memory Networks
• Character-Aware Neural Language Models - TensorFlow implementation of Character-Aware Neural Language Models
• Wavenet - This is a TensorFlow implementation of the WaveNet generative neural network architecture for audio generation.
• Mnemonic Descent Method - Tensorflow implementation of "Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment"
• CNN visualization using Tensorflow - Tensorflow implementation of "Visualizing and Understanding Convolutional Networks"
• VGAN Tensorflow - Tensorflow implementation for MIT "Generating Videos with Scene Dynamics" by Vondrick et al.
• 3D Convolutional Neural Networks in TensorFlow - Implementation of "3D Convolutional Neural Networks for Speaker Verification application" in TensorFlow by Torfi et al.
• U-Net - For Brain Tumor Segmentation
• Spatial Transformer Networks - Learn the Transformation Function
• Lip Reading - Cross Audio-Visual Recognition using 3D Architectures in TensorFlow - TensorFlow Implementation of "Cross Audio-Visual Recognition in the Wild Using Deep Learning" by Torfi et al.
• Attentive Object Tracking - Implementation of "Hierarchical Attentive Recurrent Tracking"
• Holographic Embeddings for Graph Completion and Link Prediction - Implementation of Holographic Embeddings of Knowledge Graphs
• Unsupervised Object Counting - Implementation of "Attend, Infer, Repeat"
• Tensorflow FastText - A simple embedding based text classifier inspired by Facebook's fastText.
• MusicGenreClassification - Classify music genre from a 10 second sound stream using a Neural Network.
• Kubeflow - Framework for easily using Tensorflow with Kubernetes.
• TensorNets - 40+ Popular Computer Vision Models With Pre-trained Weights.
• Ladder Network - Implementation of Ladder Network for Semi-Supervised Learning in Keras and Tensorflow
• TF-Unet - General purpose U-Network implemented in Keras for image segmentation
• Sarus TF2 Models - 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).
• Model Maker - 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.; API reference).
• DAGAN - Fast Compressed Sensing MRI Reconstruction
• Domain Transfer Network - Implementation of Unsupervised Cross-Domain Image Generation
• Show, Attend and Tell - Attention Based Image Caption Generator
• YOLO TensorFlow ++ - TensorFlow implementation of 'YOLO: Real-Time Object Detection', with training and an actual support for real-time running on mobile devices.

Official announcements

• TensorFlow: smarter machine learning, for everyone - An introduction to TensorFlow
• Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source - Release of SyntaxNet, "an open-source neural network framework implemented in TensorFlow that provides a foundation for Natural Language Understanding systems.
• TensorFlow: smarter machine learning, for everyone - An introduction to TensorFlow

Papers

• TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems - This paper describes the TensorFlow interface and an implementation of that interface that we have built at Google
• TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks
• TF.Learn: TensorFlow's High-level Module for Distributed Machine Learning
• Comparative Study of Deep Learning Software Frameworks - The study is performed on several types of deep learning architectures and we evaluate the performance of the above frameworks when employed on a single machine for both (multi-threaded) CPU and GPU (Nvidia Titan X) settings
• Distributed TensorFlow with MPI - In this paper, we extend recently proposed Google TensorFlow for execution on large scale clusters using Message Passing Interface (MPI)
• Globally Normalized Transition-Based Neural Networks - This paper describes the models behind SyntaxNet.
• TensorFlow: A system for large-scale machine learning - This paper describes the TensorFlow dataflow model in contrast to existing systems and demonstrate the compelling performance
• TensorLayer: A Versatile Library for Efficient Deep Learning Development - 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)
• TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems - This paper describes the TensorFlow interface and an implementation of that interface that we have built at Google
• Comparative Study of Deep Learning Software Frameworks - 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
• TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks
• Distributed TensorFlow with MPI - In this paper, we extend recently proposed Google TensorFlow for execution on large scale clusters using Message Passing Interface (MPI)

Powered by TensorFlow

• YOLO TensorFlow - Implementation of 'YOLO : Real-Time Object Detection'
• android-yolo - Real-time object detection on Android using the YOLO network, powered by TensorFlow.
• Magenta - Research project to advance the state of the art in machine intelligence for music and art generation

Tools/Utilities

• Speedster - Automatically apply SOTA optimization techniques to achieve the maximum inference speed-up on your hardware.
• 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.
• create-tf-app - Project builder command line tool for Tensorflow covering environment management, linting, and logging.
• Guild AI - Task runner and package manager for TensorFlow

Tutorials

• Getting Started with TensorFlow on Android - Build your first TensorFlow Android app
• CS20 SI: TensorFlow for DeepLearning Research - Stanford Course about Tensorflow from 2017 - Syllabus - Unofficial Videos
• TensorLayer - Modular implementation for TensorFlow's official tutorials. (CN).
• Understanding The Tensorflow Estimator API
• Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning - Introduction to Tensorflow offered by Coursera
• Convolutional Neural Networks in TensorFlow - Convolutional Neural Networks in Tensorflow, offered by Coursera
• TensorLayerX - Using TensorFlow like PyTorch. (Api docs)
• TensorFlow Tutorial 1 - From the basics to slightly more interesting applications of TensorFlow
• TensorFlow Tutorial 2 - Introduction to deep learning based on Google's TensorFlow framework. These tutorials are direct ports of Newmu's Theano
• TensorFlow Tutorial 3 - These tutorials are intended for beginners in Deep Learning and TensorFlow with well-documented code and YouTube videos.
• TensorFlow Examples - TensorFlow tutorials and code examples for beginners
• Sungjoon's TensorFlow-101 - TensorFlow tutorials written in Python with Jupyter Notebook
• Terry Um’s TensorFlow Exercises - Re-create the codes from other TensorFlow examples
• Installing TensorFlow on Raspberry Pi 3 - TensorFlow compiled and running properly on the Raspberry Pi
• Classification on time series - Recurrent Neural Network classification in TensorFlow with LSTM on cellphone sensor data
• Predict time series - Learn to use a seq2seq model on simple datasets as an introduction to the vast array of possibilities that this architecture offers
• Single Image Random Dot Stereograms - 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.
• TensorFlow World - Concise and ready-to-use TensorFlow tutorials with detailed documentation are provided.
• Effective Tensorflow - TensorFlow howtos and best practices. Covers the basics as well as advanced topics.

Videos

• TensorFlow Guide 1 - A guide to installation and use
• TensorFlow Guide 2 - Continuation of first video
• TensorFlow Basic Usage - A guide going over basic usage
• TensorFlow Deep MNIST for Experts - Goes over Deep MNIST
• TensorFlow Udacity Deep Learning - Basic steps to install TensorFlow for free on the Cloud 9 online service with 1Gb of data
• Why Google wants everyone to have access to TensorFlow
• Videos from TensorFlow Silicon Valley Meet Up 1/19/2016
• Videos from TensorFlow Silicon Valley Meet Up 1/21/2016
• Stanford CS224d Lecture 7 - Introduction to TensorFlow, 19th Apr 2016 - CS224d Deep Learning for Natural Language Processing by Richard Socher
• Diving into Machine Learning through TensorFlow - Pycon 2016 Portland Oregon, Slide & Code by Julia Ferraioli, Amy Unruh, Eli Bixby
• Large Scale Deep Learning with TensorFlow - Spark Summit 2016 Keynote by Jeff Dean
• Tensorflow and deep learning - without at PhD - by Martin Görner
• Tensorflow and deep learning - without at PhD, Part 2 (Google Cloud Next '17) - by Martin Görner
• Image recognition in Go using TensorFlow - by Alex Pliutau
• Image recognition in Go using TensorFlow - by Alex Pliutau
• Stanford CS224d Lecture 7 - Introduction to TensorFlow, 19th Apr 2016 - CS224d Deep Learning for Natural Language Processing by Richard Socher
• Diving into Machine Learning through TensorFlow - Pycon 2016 Portland Oregon, Slide & Code by Julia Ferraioli, Amy Unruh, Eli Bixby
• Large Scale Deep Learning with TensorFlow - Spark Summit 2016 Keynote by Jeff Dean
• TensorFlow Guide 1 - A guide to installation and use
• TensorFlow Guide 2 - Continuation of first video
• TensorFlow Basic Usage - A guide going over basic usage
• TensorFlow Deep MNIST for Experts - Goes over Deep MNIST
• Image recognition in Go using TensorFlow - by Alex Pliutau
• Why Google wants everyone to have access to TensorFlow