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
- SenseNet - Robotics touch model with TensorFlow DQN example
- Tensorflow-Project-Template - 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
- 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
- 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.
- 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
- DAGAN - 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"
- 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
- 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 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
- 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 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).
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
- 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.
- 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
- keras - 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)
- 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
- 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
- Guild AI - 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.
- 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 @jtoyAlso, 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