This article has compiled 57 of the most popular deep learning projects on GitHub (ranked by stars). Last updated: 2016.08.09

1.TensorFlow

Computes scalable machine learning problems using data flow diagrams

TensorFlow, Google’s second-generation machine learning system, performed twice as fast on some benchmarks as its first-generation DistBelief, according to the company.

TensorFlow’s extended support for built-in deep learning allows you to use TensorFlow for any computation that can be represented as a computational flow graph. Any gradient-based machine learning algorithm can benefit from the auto-differentiation of TensorFlow. It is also easy to express ideas in TensorFlow through the flexible Python interface.

2.Caffe

Stars: 11799

Caffe is a highly effective open source deep learning framework. It’s made up of expressions, speed and modularity.

3.Neural style

Stars: 10148

Torch implemented neural network algorithm.

Neural style is an algorithm that allows a machine to recreate an image by mimicking the style of an existing painting.

4.deepdream

Stars: 9042

Deep Dream, an image recognition tool

5.Keras

Stars: 7502

A deep learning library implemented by Python, including convolutional neural networks, recursive neural networks, etc. Runs on Theano and TensorFlow.

Keras is a minimalist, highly modular neural network library developed in Python (Python 2.7-3.5.) and can run on either TensorFlow or Theano platform. The good project aims to achieve rapid development of deep learning.

6.RocAlphaGo

Stars: 7170

An independent student-led project reconstructs DeepMind’s Nature 2016 paper, “Learning Go with Deep Neural Networks and Tree Search” (Nature 529, 484-489, 28 Jan 2016).

7.TensorFlow Models

Stars: 6671

A model developed based on TensorFlow

8.Neural Doodle

Stars: 6275

Turn doodles into elegant works of art with deep neural networks, generate seamless textures from photos, transform image styles, do instagram-based improvements, and more… There’s more! (Implementation of semantic style transfer)

9.CNTK

Stars: 5957

Deep learning toolkit. The CNTK toolkit from Microsoft is “crazier than anything we’ve ever seen”. This is partly thanks to CNTK’s ability to leverage graphics processing units (Gpus), which Microsoft claims to be the only company to unveil. When paired with the company’s networked GPU system, called Azure GPU Lab, it will be able to train deep neural networks to recognize speech, making the Cortana virtual assistant ten times faster than before.

10.TensorFlow Examples

Stars: 5872

TensorFlow tutorial and code examples for beginners, with notes and code explanations.

11.ConvNet JS

Stars: 5231

ConvNetJS is a neural network implemented in JavaScript, along with a browser-based demo.

12.Torch

Stars: 5133

Torch7, deep learning library.

Torch7 is a scientific computing framework that supports machine learning algorithms. It is easy to use and provides efficient algorithm implementation thanks to LuaJIT and an underlying C implementation.

13.OpenFace

Stars: 4855

Facial recognition based on deep learning network.

14.MXNet

Stars: 4685

A lightweight, portable, flexible distributed/mobile deep learning framework that supports Python, R, Julia, Scala, Go, Javascript and more.

MXNet is a deep learning framework designed for efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core is a dynamic dependency scheduler that can automatically parallel symbol and command operations. A graphical optimization layer that makes symbol execution fast and memory efficient. The library is portable, lightweight, and scalable to multiple Gpus and multiple machines.

15.Theano

Stars: 4286

Theano is a Python library that defines, optimizes, and emulates mathematical expression computations to efficiently solve multidimensional array computations.

16.Leaf

Stars: 4281

Open source machine intelligence framework for hackers.

17.Char RNN

Stars: 3820

A character-level language model for multi-level recursive neural networks, developed based on Torch.

18.Neural Talk

Stars: 3694

NeuralTalk is a Python+ Numpy project that uses multimodal recursive neural networks to describe images.

19.deeplearning4j

Stars: 3673

Java, Scala & Clojure deep learning tools based on Hadoop and Spark.

Deeplearning4j (DL4J for short) is the first commercial-grade open source distributed deep learning library written for Java and Scala. DL4J integrates with Hadoop and Spark and is designed for business environments rather than research tools. Skymind is DL4J’s business support organization.

Deeplearning4j’s advanced technology aims to plug and play, enabling rapid prototyping by non-researchers by using more presets without too much configuration. DL4J can also be customized at scale. DL4J is licensed under the Apache 2.0 license, and all derivative works based on DL4J belong to the authors of the derivative works.

20.TFLearn

Stars: 3368

Deep learning libraries, including the high-level TensorFlow interface.

21.TensorFlow Playground

Stars: 3352

Example of a neural network model.

22.OpenAI Gym

Stars: 3020

A toolkit for developing and comparing reinforcement learning algorithms.

23.Magenta

Stars: 2914

Magenta: Music and Art Generation and Machine Intelligence

A group of researchers from the Google Brain team has launched Project Magenta, whose main goal is to use machine learning to create art and compose music. Project Magenta uses the TensorFlow system, and the researchers have opened source their model and tools on GitHub.

Machine-generated music has been around for years, but it has always lacked a long narrative art, researchers say. Project Magenta tries to use stories as an important part of machine-generated music. Google released a DEMO (MP3) of the Magenta project’s results.

24.Colornet

Stars: 2798

Gray scale image is colored by neural network model.

25.Synaptic

Stars: 2666

Framework-free neural network library based on Node.js and browser.

26.Neural Talk 2

Stars: 2550

The image profile generation code developed by Torch runs on the GPU.

27.Image Analogies

Stars: 2540

Neural matching and fusion are used to generate similar patterns.

28.TensorFlow Tutorials

Stars: 2413

Tensorflow, from fundamentals to applications.

29.Lasagne

Stars: 2355

Lightweight function library based on Theano training and construction of neural network.

30.PyLearn2

Stars: 2153

Machine learning library based on Theano.

31.LISA-lab Deep Learning Tutorials

Stars: 2134

Deep learning tutorial notes and code. See the Wiki page for details.

32.Neon

Stars: 2121

Nervana™ Nervana™ is a fast, extensible and easy-to-use Python deep learning framework.

Neon is Nervana Systems’ deep learning software. Nervana’s software outperformed well-known deep learning tools, including Facebook’s own Torch7 and Nvidia’s cuDNN, according to benchmarks by a Facebook researcher.

33.Matlab Deep Learning Toolbox

Stars: 2032

Matlab/Octave deep learning toolbox. These include deep belief networks, automatic encoders, convolutional neural networks, convolutional automatic encoders, and Vanilla neural networks. There are getting started examples for each method.

34.Deep Learning Flappy Bird

Stars: 1721

Crack Flappy Bird with Deep reinforcement learning (Deep Q-learning).

35.dl-setup

Stars: 1607

Set up software instructions on the deep learning machine.

36.Chainer

Stars: 1573

A flexible neural network framework for deep learning.

Chainer is a framework for deep learning. Chainer Bridges the theoretical algorithms and practical applications of deep learning. It is characterized by being powerful, flexible and intuitive, and is considered a flexible framework for deep learning.

37.Neural Story Teller

Stars: 1514

A recursive neural network model for picture-telling.

38.DIGITS

Stars: 1353

Deep learning GPU training system.

39.Deep Jazz

Stars: 1229

Deep learning model for Generating Jazz based on Keras and Theano!

40.Tiny DNN

Stars: 1183

A deep learning framework that references only header files, has no dependencies and uses C ++ 11

41.Brainstorm

Stars: 1143

Fast, flexible and interesting neural networks.

42.dl-docker

Stars: 1044

An all-in-one Docker image for deep learning. Includes all popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.).

43.Darknet

Stars: 937

C language version of the open source neural network.

44.Theano Tutorials

Stars: 904

Introduction to Machine learning based on Theano, from linear regression to convolutional Neural networks.

45.RNN Music Composition

Stars: 904

A recursive neural network tool for generating classical music.

46.Blocks

Stars: 866

Theano framework for constructing and training neural network models

47.TDB

Stars: 860

TensorFlow’s interactive, node debugging and visualization tool.

TensorDebugger (TDB) is a deep learning debugger that extends TensorFlow (Google’s deep learning framework) using breakpoints and computer graphics to visualize real-time data streams. In particular, TDB is a combination of a Python library and a Jupyter Notebook extension that builds on Google’s TensorFlow framework.

48.Scikit Neural Net

Stars: 849

Introduction to deep neural networks tools, sciKit-learn-like classifiers and regression models.

49.Veles

Stars: 760

Distributed Machine learning Platform (Python, CUDA, OpenCL)

VELES is a distributed deep learning application. Users only need to provide parameters and VELES can do the rest. VELES is written in Python, using OpenCL or CUDA, with flow-based programming. It is another TensorFlow developed by Samsung.

50.Deep Detect

Stars: 759

Deep learning interface and server based on C++11, bundled with Python and supported Caffe.

51.TensorFlow DeepQ

Stars: 759

Deep Q learning demo based on Google Tensorflow.

52.Caffe on Spark

Stars: 724

Caffe based on Spark.

Yahoo believes that deep learning should be in the same cluster as the existing data processing pipeline that supports feature engineering and traditional (non-deep) machine learning. We created CaffeOnSpark to enable deep learning training and testing to be embedded into the Spark application. CaffeOnSpark is designed as a Spark deep learning package.

53.Nolearn

Stars: 702

Abstract neural network library, famous Lasagne.

54.DCGAN TensorFlow

Stars: 568

Deep convolutional generative adversarial network based on Tensorflow.

55.MatConvNet

Stars: 479

MATLAB CNN computer vision application toolbox.

56.DeepCL

Stars: 413

OpenCL library for training deep convolutional neural network models.

57.Visual Search Server

Stars: 304

Visual search server. A simple visual search server implemented using TensorFlow, InceptionV3 model and AWS GPU instances.

The code implements two methods, a server that handles image searches and a simple indexer that extracts pool3 functionality. Nearest neighbor searches can be performed in an approximate manner using approximations (faster) or precise methods (slower).

Source: Top Deep Learning Projects