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adding the machine learning frameworks in torch/lua

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Soumith Chintala 2014-07-16 09:44:50 -04:00
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@ -179,12 +179,66 @@ If you want to contribute to this list (please do), send me a pull request or co
#### General-Purpose Machine Learning
* [Torch7](http://torch.ch/)
* [cephes](http://jucor.github.io/torch-cephes) - Cephes mathematical functions library, wrapped for Torch. Provides and wraps the 180+ special mathematical functions from the Cephes mathematical library, developed by Stephen L. Moshier. It is used, among many other places, at the heart of SciPy.
* [graph](https://github.com/torch/graph) - Graph package for Torch
* [randomkit](http://jucor.github.io/torch-randomkit/) - Numpy's randomkit, wrapped for Torch
* [signal](http://soumith.ch/torch-signal/signal/) - A signal processing toolbox for Torch-7. FFT, DCT, Hilbert, cepstrums, stft
* [nn](https://github.com/torch/nn) - Neural Network package for Torch
* [nngraph](https://github.com/torch/nngraph) - This package provides graphical computation for nn library in Torch7.
* [nnx](https://github.com/clementfarabet/lua---nnx) - A completely unstable and experimental package that extends Torch's builtin nn library
* [optim](https://github.com/torch/optim) - An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
* [unsup](https://github.com/koraykv/unsup) - A package for unsupervised learning in Torch. Provides modules that are compatible with nn (LinearPsd, ConvPsd, AutoEncoder, ...), and self-contained algorithms (k-means, PCA).
* [manifold](https://github.com/clementfarabet/manifold) - A package to manipulate manifolds
* [svm](https://github.com/koraykv/torch-svm) - Torch-SVM library
* [lbfgs](https://github.com/clementfarabet/lbfgs) - FFI Wrapper for liblbfgs
* [vowpalwabbit](https://github.com/clementfarabet/vowpal_wabbit) - An old vowpalwabbit interface to torch.
* [OpenGM](https://github.com/clementfarabet/lua---opengm) - OpenGM is a C++ library for graphical modeling, and inference. The Lua bindings provide a simple way of describing graphs, from Lua, and then optimizing them with OpenGM.
* [sphagetti](https://github.com/MichaelMathieu/lua---spaghetti) - Spaghetti (sparse linear) module for torch7 by @MichaelMathieu
* [LuaSHKit](https://github.com/ocallaco/LuaSHkit) - A lua wrapper around the Locality sensitive hashing library SHKit
* [kernel smoothing](https://github.com/rlowrance/kernel-smoothers) - KNN, kernel-weighted average, local linear regression smoothers
* [cutorch](https://github.com/torch/cutorch) - Torch CUDA Implementation
* [cunn](https://github.com/torch/cunn) - Torch CUDA Neural Network Implementation
* [imgraph](https://github.com/clementfarabet/lua---imgraph) - An image/graph library for Torch. This package provides routines to construct graphs on images, segment them, build trees out of them, and convert them back to images.
* [videograph](https://github.com/clementfarabet/videograph) - A video/graph library for Torch. This package provides routines to construct graphs on videos, segment them, build trees out of them, and convert them back to videos.
* [saliency](https://github.com/marcoscoffier/torch-saliency) - code and tools around integral images. A library for finding interest points based on fast integral histograms.
* [stitch](https://github.com/marcoscoffier/lua---stitch) - allows us to use hugin to stitch images and apply same stitching to a video sequence
* [sfm](https://github.com/marcoscoffier/lua---sfm) - A bundle adjustment/structure from motion package
* [fex](https://github.com/koraykv/fex) - A package for feature extraction in Torch. Provides SIFT and dSIFT modules.
* [OverFeat](https://github.com/sermanet/OverFeat) - A state-of-the-art generic dense feature extractor
* [Numeric Lua](http://numlua.luaforge.net/)
* [Lunatic Python](http://labix.org/lunatic-python)
* [SciLua](http://www.scilua.org/)
* [Lua - Numerical Algorithms](https://bitbucket.org/lucashnegri/lna)
* [Lunum](http://zrake.webfactional.com/projects/lunum)
#### Demos and Scripts
* [Core torch7 demos repository](https://github.com/e-lab/torch7-demos).
* linear-regression, logistic-regression
* face detector (training and detection as separate demos)
* mst-based-segmenter
* train-a-digit-classifier
* train-autoencoder
* optical flow demo
* train-on-housenumbers
* train-on-cifar
* tracking with deep nets
* kinect demo
* filter-bank visualization
* saliency-networks
* [Training a Convnet for the Galaxy-Zoo Kaggle challenge(CUDA demo)](https://github.com/soumith/galaxyzoo)
* [Music Tagging](https://github.com/mbhenaff/MusicTagging) - Music Tagging scripts for torch7
* [torch-datasets](https://github.com/rosejn/torch-datasets) - Scripts to load several popular datasets including:
* BSR 500
* CIFAR-10
* COIL
* Street View House Numbers
* MNIST
* NORB
* [Atari2600](https://github.com/fidlej/aledataset) - Scripts to generate a dataset with static frames from the Arcade Learning Environment
## Matlab
#### Computer Vision