A curated list of awesome TensorFlow experiments, libraries, and projects. Inspired by awesome-machine-learning.
What is TensorFlow?
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.
More info here.
Table of Contents
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 tutorials and code examples for beginners
- 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
Getting Started with TensorFlow on Android
- 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.
CS20 SI: TensorFlow for DeepLearning Research
- Stanford Course about Tensorflow from 2017 - Syllabus
- Unofficial Videos
- Concise and ready-to-use TensorFlow tutorials with detailed documentation are provided.
- TensorFlow howtos and best practices. Covers the basics as well as advanced topics.
- Modular implementation for TensorFlow's official tutorials. (CN
Understanding The Tensorflow Estimator API
A conceptual overview of the Estimator API, when you'd use it and why.
Convolutional Neural Networks in TensorFlow
- Convolutional Neural Networks in Tensorflow, offered by Coursera
- Robotics touch model with TensorFlow DQN example
- A simple and well-designed template for your tensorflow project.
Domain Transfer Network
- Implementation of Unsupervised Cross-Domain Image Generation
Show, Attend and Tell
- Attention Based Image Caption Generator
Implementation of Neural Style
- Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
- Pretty Tensor provides a high level builder API
- An implementation of neural style
- 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
- Implementation of A Neural Algorithm of Artistic Style
Deep-Q learning Pong with TensorFlow and PyGame
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.
- Implementation of "A neural conversational model"
- Chatbot in 200 lines of code
- Deep Convolutional Generative Adversarial Networks
-Generative Adversarial Text to Image Synthesis
- Unsupervised Image to Image Translation with Generative Adversarial Networks
- Unpaired Image to Image Translation
- Fast Compressed Sensing MRI Reconstruction
Colornet - Neural Network to colorize grayscale images
- Neural Network to colorize grayscale images
Neural Caption Generator
- Implementation of "Show and Tell"
Neural Caption Generator with Attention
- Implementation of "Show, Attend and Tell"
- 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
- Train TensorFlow neural nets with OpenStreetMap features and satellite imagery.
- TensorFlow implementation of DeepMind's 'Human-Level Control through Deep Reinforcement Learning' with OpenAI Gym by Devsisters.com
- For Playing Atari Ping Pong
- For Playing Frozen Lake Game
- Actor Critic for Playing Discrete Action space Game (Cartpole)
- Asynchronous Advantage Actor Critic (A3C) for Continuous Action Space (Bipedal Walker)
- For Playing Gym Torcs
- For Continuous and Discrete Action Space by
- 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
YOLO TensorFlow ++
- TensorFlow implementation of 'YOLO: Real-Time Object Detection', with training and an actual support for real-time running on mobile devices.
- 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"
- 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.
- 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"
- A simple embedding based text classifier inspired by Facebook's fastText.
- Classify music genre from a 10 second sound stream using a Neural Network.
- Framework for easily using Tensorflow with Kubernetes.
- 40+ Popular Computer Vision Models With Pre-trained Weights.
- Implementation of Ladder Network for Semi-Supervised Learning in Keras and Tensorflow
- Implementation of 'YOLO : Real-Time Object Detection'
- 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
- 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.
- Implementation of Monotonic Calibrated Interpolated Look-Up Tables in TensorFlow
- TensorFlow native interface for ruby using SWIG
- Deep learning library featuring a higher-level API
- Deep learning and reinforcement learning library for researchers and engineers
- High-level library for defining models
- TensorFlow binding for Apache Spark
- TensorForce: A TensorFlow library for applied reinforcement learning
- initiative from Yahoo! to enable distributed TensorFlow with Apache Spark.
- 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 Globally Normalized Transition-Based Neural Networks, Andor et al. (2016)
- Run Keras models (tensorflow backend) in the browser, with GPU support
- Simple framework allowing to read-in ROOT NTuples by converting them to a Numpy array and then use them in Google Tensorflow.
- Sonnet is DeepMind's library built on top of TensorFlow for building complex neural networks.
- 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
- Convert PyTorch models to Keras (with TensorFlow backend) format
- Convert Gluon models to Keras (with TensorFlow backend) format
- Lightweight, cross-platform library for deploying TensorFlow Lite models to mobile devices.
- Machine Learning on Graphs, a Python library for machine learning on graph-structured (network-structured) data.
- Task runner and package manager for TensorFlow
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
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
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: 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 on Twitter
Machine Learning with TensorFlow
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.
First Contact with TensorFlow
by Jordi Torres, professor at UPC Barcelona Tech and a research manager and senior advisor at Barcelona Supercomputing Center
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
– 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).
Building Machine Learning Projects with 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.
Deep Learning using TensorLayer
- by Hao Dong et al. This book covers both deep learning and the implmentation by using TensorFlow and TensorLayer.
Your contributions are always welcome!
If you want to contribute to this list (please do), send me a pull request or contact me @jtoy
Also, if you notice that any of the above listed repositories should be deprecated, due to any of the following reasons:
- Repository's owner explicitly say that "this library is not maintained".
- Not committed for long time (2~3 years).
More info on the guidelines
Some of the python libraries were cut-and-pasted from vinta
The few go reference I found where pulled from this page