awesome-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

Build your first TensorFlow Android app

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

Stanford Course about Tensorflow from 2017 - -

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

Modular implementation for TensorFlow's official tutorials. ( )

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

Introduction to Tensorflow offered by Coursera

Convolutional Neural Networks in Tensorflow, offered by Coursera

Using TensorFlow like PyTorch. ( )

Domain Transfer Network

Implementation of Unsupervised Cross-Domain Image Generation

Show, Attend and Tell

Attention Based Image Caption Generator

Neural Style

Implementation of 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

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

DAGAN

Fast Compressed Sensing MRI Reconstruction

Colornet - Neural Network to colorize grayscale images

Neural Network to colorize grayscale images

Neural Caption Generator

Implementation of

Neural Caption Generator with Attention

Implementation of

Weakly_detector

Implementation of

Dynamic Capacity Networks

Implementation of

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

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)

DAGGER

For Playing

TRPO

For Continuous and Discrete Action Space by

Highway Network

TensorFlow implementation of with a

Hierarchical Attention Networks

TensorFlow implementation of

Sentence Classification with CNN

TensorFlow implementation of with a

End-To-End Memory Networks

Implementation of

Character-Aware Neural Language Models

TensorFlow implementation of

YOLO TensorFlow ++

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

Wavenet

This is a TensorFlow implementation of the for audio generation

Mnemonic Descent Method

Tensorflow implementation of

CNN visualization using Tensorflow

Tensorflow implementation of

VGAN Tensorflow

Tensorflow implementation for MIT by Vondrick et al

3D Convolutional Neural Networks in TensorFlow

Implementation of 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 by Torfi et al

Attentive Object Tracking

Implementation of

Holographic Embeddings for Graph Completion and Link Prediction

Implementation of

Unsupervised Object Counting

Implementation of

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)

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.; )

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

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

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

TensorLayer

Deep learning and reinforcement learning library for researchers and engineers

TensorFlow-Slim

High-level library for defining models

TensorFrames

TensorFlow binding for Apache Spark

TensorForce

TensorForce: A TensorFlow library for applied reinforcement learning

TensorFlowOnSpark

initiative from Yahoo! to enable distributed TensorFlow with Apache Spark

caffe-tensorflow

Convert Caffe models to TensorFlow format

Minimal, modular deep learning library for TensorFlow and Theano

SyntaxNet: Neural Models of Syntax

A TensorFlow implementation of the models described in

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

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

tf-encrypted

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

pytorch2keras

Convert PyTorch models to Keras (with TensorFlow backend) format

gluon2keras

Convert Gluon models to Keras (with TensorFlow backend) format

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

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

TensorLayerX

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

Task runner and package manager for TensorFlow

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

Continuation of first video

A guide going over basic usage

Goes over Deep MNIST

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

CS224d Deep Learning for Natural Language Processing by Richard Socher

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

Spark Summit 2016 Keynote by Jeff Dean

by Martin Görner

by Martin Görner

by Alex Pliutau

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

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

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)

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

Goes over the implementation of TensorFlow

Key Features Illustrated

Understanding the Internals of TensorFlow Learn Estimators

A survey of six months rapid evolution (+ tips/hacks and code to fix the ugly stuff), Dan Kuster at Indico, May 9, 2016

A joke by Joel Grus

Step-by-step guide with full code examples on GitHub

semantic segmentation and handling the TFRecord file format

Android TensorFlow Machine Learning Example

Introduces TensorFlow optimizations on Intel® Xeon® and Intel® Xeon Phi™ processor-based platforms based on an Intel/Google collaboration

Coca-Cola's product code image recognizing neural network with user input feedback loop

How Does The Machine Learning Library TensorFlow Work?

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

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

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

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 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

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

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)

The few go reference I found where pulled from