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DeepLearnToolBox is a matlab/octave toolbox for deep learning and includes Deep Belief Nets, Stacked Autoencoders, convolutional neural nets.
cuda-convnet is a fast C++/CUDA implementation of convolutional (or more generally, feed-forward) neural networks. It can model arbitrary layer connectivity and network depth. Any directed acyclic graph of layers will do. Training is done using the backpropagation algorithm.
MatConvNet is a MATLAB toolbox implementing Convolutional Neural Networks (CNNs) for computer vision applications. It is simple, efficient, and can run and learn state-of-the-art CNNs
eblearn is an open-source C++ library of machine learning by New York University’s machine learning lab, led by Yann LeCun.
SINGA is designed to be general to implement the distributed training algorithms of existing systems.
NVIDIA DIGITS is a new system for developing, training and visualizing deep neural networks.
Intel® Deep Learning Framework provides a unified framework for Intel® platforms accelerating Deep Convolutional Neural Networks.
N-Dimensional Arrays for Java (ND4J)is scientific computing libraries for the JVM.
Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala.
Encog is an advanced machine learning framework which supports Support Vector Machines,Artificial Neural Networks, Genetic Programming, Bayesian Networks, Hidden Markov Models, Genetic Programming and Genetic Algorithms are supported.
Torch is a scientific computing framework with wide support for machine learning algorithms.
Mocha is a Deep Learning framework for Julia, inspired by the C++ framework Caffe.
Lush(Lisp Universal Shell) is an object-oriented programming language designed for researchers, experimenters, and engineers interested in large-scale numerical and graphic applications.
DNNGraph is a deep neural network model generation DSL in Haskell.
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