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Currently, Torch is developed at IDIAP, in Switzerland and at Universite de Montreal in Québec.
The Torch Team (Author)
Ronan Collobert, collober@iro.umontreal.ca(Main Contributors)
Samy Bengio, bengio@idiap.ch
Johnny Mariethoz, marietho@idiap.ch
It's a machine-learning library, written in C++.
It's distributed under the GPL licence.It is, and it will be in development forever.
It's for Unix and Linux systems: other systems aren't supported at all.
It has been successfully compiled on Linux, SunOS, FreeBSD and OSF1.Currently, the main features are the following:
As it's an open library, we encourage everybody to develop new packages which could then be included in future versions on the official website (as long as it follows the coding guidelines).
- A lot of things in gradient-machines, that is, machines which could be learned with gradient descent. This includes Multi-Layered Perceptrons, Radial Basis Functions and Mixtures of Experts. In fact there are a lot of small "modules" available (Linear module, Tanh module, SoftMax module...) that you can plug as you want to get what you want.
- Support Vector Machine, in classification and regression.
- A Distribution package which includes Kmeans, Gaussian Mixture Models, Hidden Markov Models and Bayes Classifier. Moreover classes for speech recognition with embedded training are available is this package.
- Ensemble models such as Bagging and Adaboost.
- A few non-parametric models such as K-nearest-neighbors, Parzen Regression and Parzen Density Estimator.
The aim of Torch is to provide the state-of-the-art of the best algorithms in machine learning. Therefore...... Torch is made for you!
- If you know C++,
- If you're working in machine learning and want to develop your own algorithms,
- or if you want to use well-known machine-learning algorithms