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Merge pull request #30 from soumith/master
adding the machine learning frameworks in torch/lua
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README.md
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README.md
@ -181,12 +181,66 @@ If you want to contribute to this list (please do), send me a pull request or co
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#### General-Purpose Machine Learning
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* [Torch7](http://torch.ch/)
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* [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.
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* [graph](https://github.com/torch/graph) - Graph package for Torch
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* [randomkit](http://jucor.github.io/torch-randomkit/) - Numpy's randomkit, wrapped for Torch
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* [signal](http://soumith.ch/torch-signal/signal/) - A signal processing toolbox for Torch-7. FFT, DCT, Hilbert, cepstrums, stft
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* [nn](https://github.com/torch/nn) - Neural Network package for Torch
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* [nngraph](https://github.com/torch/nngraph) - This package provides graphical computation for nn library in Torch7.
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* [nnx](https://github.com/clementfarabet/lua---nnx) - A completely unstable and experimental package that extends Torch's builtin nn library
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* [optim](https://github.com/torch/optim) - An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
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* [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).
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* [manifold](https://github.com/clementfarabet/manifold) - A package to manipulate manifolds
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* [svm](https://github.com/koraykv/torch-svm) - Torch-SVM library
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* [lbfgs](https://github.com/clementfarabet/lbfgs) - FFI Wrapper for liblbfgs
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* [vowpalwabbit](https://github.com/clementfarabet/vowpal_wabbit) - An old vowpalwabbit interface to torch.
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* [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.
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* [sphagetti](https://github.com/MichaelMathieu/lua---spaghetti) - Spaghetti (sparse linear) module for torch7 by @MichaelMathieu
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* [LuaSHKit](https://github.com/ocallaco/LuaSHkit) - A lua wrapper around the Locality sensitive hashing library SHKit
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* [kernel smoothing](https://github.com/rlowrance/kernel-smoothers) - KNN, kernel-weighted average, local linear regression smoothers
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* [cutorch](https://github.com/torch/cutorch) - Torch CUDA Implementation
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* [cunn](https://github.com/torch/cunn) - Torch CUDA Neural Network Implementation
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* [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.
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* [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.
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* [saliency](https://github.com/marcoscoffier/torch-saliency) - code and tools around integral images. A library for finding interest points based on fast integral histograms.
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* [stitch](https://github.com/marcoscoffier/lua---stitch) - allows us to use hugin to stitch images and apply same stitching to a video sequence
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* [sfm](https://github.com/marcoscoffier/lua---sfm) - A bundle adjustment/structure from motion package
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* [fex](https://github.com/koraykv/fex) - A package for feature extraction in Torch. Provides SIFT and dSIFT modules.
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* [OverFeat](https://github.com/sermanet/OverFeat) - A state-of-the-art generic dense feature extractor
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* [Numeric Lua](http://numlua.luaforge.net/)
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* [Lunatic Python](http://labix.org/lunatic-python)
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* [SciLua](http://www.scilua.org/)
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* [Lua - Numerical Algorithms](https://bitbucket.org/lucashnegri/lna)
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* [Lunum](http://zrake.webfactional.com/projects/lunum)
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#### Demos and Scripts
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* [Core torch7 demos repository](https://github.com/e-lab/torch7-demos).
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* linear-regression, logistic-regression
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* face detector (training and detection as separate demos)
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* mst-based-segmenter
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* train-a-digit-classifier
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* train-autoencoder
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* optical flow demo
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* train-on-housenumbers
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* train-on-cifar
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* tracking with deep nets
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* kinect demo
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* filter-bank visualization
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* saliency-networks
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* [Training a Convnet for the Galaxy-Zoo Kaggle challenge(CUDA demo)](https://github.com/soumith/galaxyzoo)
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* [Music Tagging](https://github.com/mbhenaff/MusicTagging) - Music Tagging scripts for torch7
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* [torch-datasets](https://github.com/rosejn/torch-datasets) - Scripts to load several popular datasets including:
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* BSR 500
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* CIFAR-10
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* COIL
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* Street View House Numbers
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* MNIST
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* NORB
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* [Atari2600](https://github.com/fidlej/aledataset) - Scripts to generate a dataset with static frames from the Arcade Learning Environment
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## Matlab
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#### Computer Vision
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