TensorFlow

– 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.

by Hao Dong et al. This book covers both deep learning and the implementation by using TensorFlow and TensorLayer.

Develop Deep Learning Models on Theano and TensorFlow Using Keras by Jason Brownlee

by Jordi Torres, professor at UPC Barcelona Tech and a research manager and senior advisor at Barcelona Supercomputing Center

Get up and running with the latest numerical computing library by Google and dive deeper into your data, by Giancarlo Zaccone

– 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).

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.

by Cameron Davidson-Pilon. Introduction to Bayesian methods and probabilistic graphical models using tensorflow-probability (and, alternatively PyMC2/3).

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.

Complete guide to use TensorFlow from the basics of graph computing, to deep learning models to using it in production environments - Bleeding Edge Press

The few go reference I found where pulled from

Some of the python libraries were cut-and-pasted from

Convert Caffe models to TensorFlow format

High-Level Keras Complement for implement common architectures stacks, served as easy to use plug-n-play modules

Convert Gluon models to Keras (with TensorFlow backend) format

Minimal, modular deep learning library for TensorFlow and Theano

Run Keras models (tensorflow backend) in the browser, with GPU support

Implementation of Monotonic Calibrated Interpolated Look-Up Tables in TensorFlow

Simple framework allowing to read-in ROOT NTuples by converting them to a Numpy array and then use them in Google Tensorflow.

Convert PyTorch models to Keras (with TensorFlow backend) format

R interface to TensorFlow APIs, including Estimators, Keras, Datasets, etc.

Sonnet is DeepMind's library built on top of TensorFlow for building complex neural networks.

Machine Learning on Graphs, a Python library for machine learning on graph-structured (network-structured) data.

A TensorFlow implementation of the models described in Globally Normalized Transition-Based Neural Networks, Andor et al. (2016)

high-level TensorFlow API that greatly simplifies machine learning programming (originally tensorflow/skflow)

Probabilistic programming built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware.

High-level library for defining models

TensorFlow native interface for ruby using SWIG

initiative from Yahoo! to enable distributed TensorFlow with Apache Spark.

TensorForce: A TensorFlow library for applied reinforcement learning

TensorFlow binding for Apache Spark

Lightweight, cross-platform library for deploying TensorFlow Lite models to mobile devices.

Deep learning and reinforcement learning library for researchers and engineers

TensorLayerX: A Unified Deep Learning Framework for All Hardwares, Backends and OS, including TensorFlow.

Neural Network Toolbox on TensorFlow focusing on training speed and on large datasets.

Layer on top of TensorFlow for doing machine learning on encrypted data

Deep learning library featuring a higher-level API

A modern C++ wrapper for TensorFlow.

Implementation of "3D Convolutional Neural Networks for Speaker Verification application" in TensorFlow by Torfi et al.

Asynchronous Advantage Actor Critic (A3C) for Continuous Action Space (Bipedal Walker)

Actor Critic for Playing Discrete Action space Game (Cartpole)

An implementations of AlexNet3D. Simple AlexNet model but with 3D convolutional layers (conv3d).

Implementation of "Hierarchical Attentive Recurrent Tracking"

TensorFlow implementation of Character-Aware Neural Language Models

Implementation of "A neural conversational model"

Tensorflow implementation of "Visualizing and Understanding Convolutional Networks"

Neural Network to colorize grayscale images

Fast Compressed Sensing MRI Reconstruction

For Playing Gym Torcs

Deep Convolutional Generative Adversarial Networks

For Playing Frozen Lake Game

Train TensorFlow neural nets with OpenStreetMap features and satellite imagery.

Implementation of Unsupervised Cross-Domain Image Generation

TensorFlow implementation of DeepMind's 'Human-Level Control through Deep Reinforcement Learning' with OpenAI Gym by Devsisters.com

Implementation of "Dynamic Capacity Networks"

Implementation of End-To-End Memory Networks

Generative Adversarial Text to Image Synthesis

An attempt to implement the random handwriting generation portion of Alex Graves' paper

Search, filter, and describe videos based on objects, places, and other things that appear in them

TensorFlow implementation of "Hierarchical Attention Networks for Document Classification"

TensorFlow implementation of "Training Very Deep Networks" with a blog post

Implementation of viterbi and forward/backward algorithms for HMM

Implementation of Holographic Embeddings of Knowledge Graphs

Unsupervised Image to Image Translation with Generative Adversarial Networks

Unpaired Image to Image Translation

Framework for easily using Tensorflow with Kubernetes.

Implementation of Ladder Network for Semi-Supervised Learning in Keras and Tensorflow

TensorFlow Implementation of "Cross Audio-Visual Recognition in the Wild Using Deep Learning" by Torfi et al.

Tensorflow implementation of "Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment"

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).

Classify music genre from a 10 second sound stream using a Neural Network.

Implementation of "Show and Tell"

Implementation of "Show, Attend and Tell"

This performs a monolingual translation, going from modern English to Shakespeare and vice-versa.

Implementation of Neural Style

An implementation of neural style

implementation of Neural Turing Machine

Implementation of A Neural Algorithm of Artistic Style

For Playing Atari Ping Pong

Pretty Tensor provides a high level builder API

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).

TensorFlow implementation of "Convolutional Neural Networks for Sentence Classification" with a blog post

Chatbot in 200 lines of code

Attention Based Image Caption Generator

Learn the Transformation Function

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

A simple embedding based text classifier inspired by Facebook's fastText.

Annotated notes and summaries of the TensorFlow white paper, along with SVG figures and links to documentation

A simple and well-designed template for your tensorflow project.

40+ Popular Computer Vision Models With Pre-trained Weights.

General purpose U-Network implemented in Keras for image segmentation

For Continuous and Discrete Action Space by

For Brain Tumor Segmentation

Implementation of "Attend, Infer, Repeat"

Tensorflow implementation for MIT "Generating Videos with Scene Dynamics" by Vondrick et al.

This is a TensorFlow implementation of the WaveNet generative neural network architecture for audio generation.

Implementation of "Learning Deep Features for Discriminative Localization"

TensorFlow implementation of 'YOLO: Real-Time Object Detection', with training and an actual support for real-time running on mobile devices.

Release of SyntaxNet, "an open-source neural network framework implemented in TensorFlow that provides a foundation for Natural Language Understanding systems.

An introduction to TensorFlow

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

In this paper, we extend recently proposed Google TensorFlow for execution on large scale clusters using Message Passing Interface (MPI)

This paper describes the models behind SyntaxNet.

This paper describes the TensorFlow dataflow model in contrast to existing systems and demonstrate the compelling performance

This paper describes the TensorFlow interface and an implementation of that interface that we have built at Google

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)

Real-time object detection on Android using the YOLO network, powered by TensorFlow.

Research project to advance the state of the art in machine intelligence for music and art generation

Implementation of 'YOLO : Real-Time Object Detection'

Project builder command line tool for Tensorflow covering environment management, linting, and logging.

Task runner and package manager for TensorFlow

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.

Automatically apply SOTA optimization techniques to achieve the maximum inference speed-up on your hardware.

Recurrent Neural Network classification in TensorFlow with LSTM on cellphone sensor data

Convolutional Neural Networks in Tensorflow, offered by Coursera

Stanford Course about Tensorflow from 2017 - Syllabus - Unofficial Videos

TensorFlow howtos and best practices. Covers the basics as well as advanced topics.

Build your first TensorFlow Android app

TensorFlow compiled and running properly on the Raspberry Pi

Introduction to Tensorflow offered by Coursera

Learn to use a seq2seq model on simple datasets as an introduction to the vast array of possibilities that this architecture offers

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 tutorials written in Python with Jupyter Notebook

TensorFlow tutorials and code examples for beginners

From the basics to slightly more interesting applications of TensorFlow

Introduction to deep learning based on Google's TensorFlow framework. These tutorials are direct ports of Newmu's Theano

These tutorials are intended for beginners in Deep Learning and TensorFlow with well-documented code and YouTube videos.

Concise and ready-to-use TensorFlow tutorials with detailed documentation are provided.

Modular implementation for TensorFlow's official tutorials. (CN).

Using TensorFlow like PyTorch. (Api docs)

Re-create the codes from other TensorFlow examples

A conceptual overview of the Estimator API, when you'd use it and why.

Pycon 2016 Portland Oregon, Slide & Code by Julia Ferraioli, Amy Unruh, Eli Bixby

by Alex Pliutau

Spark Summit 2016 Keynote by Jeff Dean

CS224d Deep Learning for Natural Language Processing by Richard Socher

by Martin Görner

by Martin Görner

A guide going over basic usage

Goes over Deep MNIST

A guide to installation and use

Continuation of first video

Basic steps to install TensorFlow for free on the Cloud 9 online service with 1Gb of data