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DL Libraries

Note: Deep fried!

Python

http://deeplearning.net/software/theano/ Theano is a python library for defining and evaluating mathematical expressions with numerical arrays.

https://keras.io/ Keras is a minimalist, highly modular neural network library in the spirit of Torch, written in Python, that uses Theano under the hood for optimized tensor manipulation on GPU and CPU.

http://deeplearning.net/software/pylearn2/ Pylearn2 is a library that wraps a lot of models and training algorithms such as Stochastic Gradient Descent that are commonly used in Deep Learning.

https://github.com/Lasagne/Lasagne Lasagne is a lightweight library to build and train neural networks in Theano.

https://github.com/mila-iqia/blocks Blocks a framework that helps you build neural network models on top of Theano.

http://caffe.berkeleyvision.org/ Caffe is a deep learning framework made with expression, speed, and modularity in mind.

https://github.com/dnouri/nolearn nolearn contains a number of wrappers and abstractions around existing neural network libraries, most notably Lasagne, along with a few machine learning utility modules.

https://radimrehurek.com/gensim/ Gensim is deep learning toolkit implemented in python programming language intended for handling large text collections, using efficient algorithms.

https://chainer.org/ Chainer bridge the gap between algorithms and implementations of deep learning.

https://github.com/nitishsrivastava/deepnet deepnet is a GPU-based python implementation of deep learning algorithms like Feed-forward Neural Nets, Restricted Boltzmann Machines, Deep Belief Nets, Autoencoders, Deep Boltzmann Machines and Convolutional Neural Nets.

https://github.com/hannes-brt/hebel Hebel is a library for deep learning with neural networks in Python using GPU acceleration with CUDA through PyCUDA.

https://github.com/dmlc/cxxnet CXXNET is fast, concise, distributed deep learning framework based on MShadow.

https://github.com/apache/incubator-mxnet Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

https://github.com/andersbll/deeppy DeepPy is a Pythonic deep learning framework built on top of NumPy.

https://github.com/vishwa-raman/DeepLearning DeepLearning is deep learning library, developed with C++ and python.

https://github.com/NervanaSystems/neon Neon is Nervana’s Python based Deep Learning framework.

Lua

http://torch.ch/ Torch is a scientific computing framework with wide support for machine learning algorithms.

Julia

https://github.com/pluskid/Mocha.jl Deep Learning framework for Julia Mocha is a Deep Learning framework for Julia, inspired by the C++ framework Caffe.

Lisp

http://lush.sourceforge.net/ Lush(Lisp Universal Shell) is an object-oriented programming language designed for researchers, experimenters, and engineers interested in large-scale numerical and graphic applications.

R

DNNGraph https://github.com/ajtulloch/dnngraph https://www.rdocumentation.org/packages/darch/versions/0.12.0 DNNGraph is a deep neural network model generation DSL in Haskell.

https://cran.r-project.org/web/packages/deepnet/index.html deepnet implements some deep learning architectures and neural network algorithms, including BP,RBM,DBN,Deep autoencoder and so on.

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