Description:

Torch is a simple machine-learning library, among its features you can find:

* A lot of things in gradient machines, that is, machines which could be
learned with a gradient descent. This includes multi-layered perceptrons,
radial bas is functions, mixtures of experts, convolutional networks and
even time-delay neural networks. In fact a lot of "modules" are available
that you can plug as you want to get what you need.
* Support vector machines, in classification and regression. As fast as the
old stand-alone program SVMTorch II, but with the powerful environment of
the library.
* Ensemble models such as bagging or adaboost.
* Non-parametric models such as K-nearest-neighbors, Parzen regression and
Parzen density estimator.
* Distributions stuff, like Kmeans, Gaussian mixture models, hidden Markov
models, input-output hidden Markov models, and Bayes classifier.
* Speech recognition tools (Embedded training and large vocabulary decoding).