Comparison of deep learning software/Resources

This page lists resources that can be useful to the Comparison of deep learning software page.

Deep learning software not yet covered

This is a list of deep learning software that is not listed on the main page because they lack a Wikipedia article. If you would like to see any of these pieces of software listed there, you are welcome to create a Wikipedia article for it.

• adnn – Javascript neural networks
• Blocks – Theano framework for building and training neural networks
• Caffe2 – Deep learning framework built on Caffe, developed by Facebook in cooperation with NVIDIA, Qualcomm, Intel, Amazon, and Microsoft^[1]
• CaffeOnSpark – Scalable deep learning package running Caffe on Spark and Hadoop clusters with peer-to-peer communication
• CNNLab – Deep learning framework using GPU and FPGA-based accelerators
• ConvNetJS – Javascript library for training deep learning models entirely in a web browser
• Cortex – Theano-based deep learning toolbox for neuroimaging
• cuDNN – Optimized deep learning computation primitives implemented in CUDA
• CURRENNT – CUDA-accelerated toolkit for deep Long Short-Term Memory (LSTM) RNN architectures supporting large data sets not fitting into main memory.
• DeepCL – OpenCL library to train deep convolutional networks, with APIs for C++, Python and the command line
• DeepLearningKit – Open source deep learning framework for iOS, OS X and tvOS^[2]
• DeepLearnToolbox – Matlab/Octave toolbox for deep learning (deprecated)
• DeepX – Software accelerator for deep learning execution aimed towards mobile devices
• deepy – Extensible deep learning framework based on Theano
• DSSTNE (Deep Scalable Sparse Tensor Network Engine) – Amazon developed library for building deep learning models
• Faster RNNLM (HS/NCE) toolkit – An rnnlm implementation for training on huge datasets and very large vocabularies and usage in real-world ASR and MT problems
• GNU Gneural Network – GNU package which implements a programmable neural network
• IDLF – Intel® Deep Learning Framework; supports OpenCL (deprecated)
• Intel Math Kernel Library (Intel MKL),^[3] library of optimized math routines, including optimized deep learning computation primitives
• Keras – Deep Learning library for Theano and TensorFlow
• Lasagne – Lightweight library to build and train neural networks in Theano
• Leaf – "The Hacker's Machine Learning Engine"; supports OpenCL (official development suspended^[4])
• LightNet – MATLAB-based environment for deep learning
• MatConvNet – CNNs for MATLAB
• MaTEx – Distributed TensorFlow with MPI by PNNL
• Mocha – Deep learning framework for Julia, inspired by Caffe
• neon – Nervana's Python based Deep Learning framework
• Neural Network Toolbox – MATLAB toolbox for neural network creation, training and simulation
• PaddlePaddle – "PArallel Distributed Deep LEarning", deep learning platform
• Purine – Bi-graph based deep learning framework^[5]
• Pylearn2 – Machine learning library mainly built on top of Theano
• Pytorch - Python based implementation of Torch API, allows for dynamic graph construction
• scikit-neuralnetwork – Multi-layer perceptrons as a wrapper for Pylearn2
• sklearn-theano – Scikit-learn compatible tools using theano
• Tensor Builder – Lightweight extensible library for easy creation of deep neural networks using functions from "any Tensor-based library" (requires TensorFlow) through an API based on the Builder Pattern
• TensorGraph – Framework for building any models based on TensorFlow
• TF Learn (Scikit Flow) – Simplified interface for TensorFlow
• TF-Slim – High level library to define complex models in TensorFlow
• TFLearn – Deep learning library featuring a higher-level API for TensorFlow
• Theano-Lights – Deep learning research framework based on Theano
• tiny-dnn – Header only, dependency-free deep learning framework in C++11
• torchnet – Torch framework providing a set of abstractions aiming at encouraging code re-use as well as encouraging modular programming^[6][7]
• Veles – Distributed machine learning platform by Samsung

Related software

• Deep Visualization Toolbox^[8][9] – Software tool for "probing" DNNs by feeding them image data and watching the reaction of every neuron, and for visualizing what a specific neuron "wants to see the most"
• LSTMVis – A visual analysis tool for recurrent neural networks
• pastalog – Simple, realtime visualization of neural network training performance

References

External links

• GitHub machine learning showcase
• Popular Deep Learning Tools – a review
• 50 Deep Learning Software Tools and Platforms
• Comparative study of Caffe, Neon, TensorFlow, Theano, and Torch
• Software links
• Deep Learning Libraries by Language
• DL4J vs. Torch vs. Theano vs. Caffe vs. TensorFlow
• Evaluation of Deep Learning Toolkits, an evaluation of Caffe, CNTK, TensorFlow, Theano, and Torch with ratings on different aspects
• YouTube: CS231n Winter 2016: Lecture 12: Deep Learning libraries – A comparison of Caffe, Torch, Theano and Tensorflow
• 10 Most Popular Deep Learning Libraries Started in 2015
• 13 frameworks for mastering machine learning
• Want an open-source deep learning framework? Take your pick
• What is the best deep learning library at the current stage for working on large data?
• Awesome Machine Learning – A large list of machine learning frameworks, libraries and software by language
• 15 Deep Learning Libraries – 15 libraries in various languages
• TensorFlow Meets Microsoft’s CNTK – Comparison of TensorFlow and CNTK
• Deep Learning Frameworks – Short list of deep learning frameworks recommended by Nvidia
• Awesome TensorFlow – Libraries
• Popular Deep Learning Libraries