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
- adnn – Javascript neural networks
- Blocks – Theano framework for building and training neural networks
- 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[1]
- 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),[2] 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[3])
- LightNet – MATLAB-based environment for deep learning
- MatConvNet – CNNs for MATLAB
- MaTEx – Distributed TensorFlow with MPI by PNNL
- 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 by Baidu
- Purine – Bi-graph based deep learning framework[4]
- Pylearn2 – Machine learning library mainly built on top of Theano
- 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[5][6]
- Veles – Distributed machine learning platform by Samsung
Related software
- Deep Visualization Toolbox[7][8] – 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
- ↑ http://arxiv.org/pdf/1605.04614v1.pdf
- ↑ https://software.intel.com/en-us/articles/introducing-dnn-primitives-in-intelr-mkl
- ↑ Michael Hirn (9 May 2016). "Tensorflow wins". Retrieved 17 August 2016.
... I will suspend the development of Leaf and focus on new ventures.
- ↑ https://arxiv.org/abs/1412.6249
- ↑ https://code.facebook.com/posts/580706092103929
- ↑ Ronan Collobert; Laurens van der Maaten; Armand Joulin. "Torchnet: An Open-Source Platform for (Deep) Learning Research" (PDF). Facebook AI Research. Retrieved 24 June 2016.
- ↑ http://arxiv.org/abs/1506.06579
- ↑ http://yosinski.com/deepvis
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
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