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libtorch3-dev

State of the art machine learning library - development files

Variants:
Torch is a machine-learning library, written in C++. Its aim is to provide the state-of-the-art of the best algorithms.

* Many gradient-based methods, including multi-layered perceptrons, radial basis functions, and mixtures of experts. Many small "modules" (Linear module, Tanh module, SoftMax module, ...) can be plugged together. * Support Vector Machine, for classification and regression. * Distribution package, includes Kmeans, Gaussian Mixture Models, Hidden Markov Models, and Bayes Classifier, and classes for speech recognition with embedded training. * Ensemble models such as Bagging and Adaboost. * Non-parametric models such as K-nearest-neighbors, Parzen Regression and Parzen Density Estimator.

This package is the Torch development package (header files and static library.)

Homepage:-
Package version:3.1-1.1
Architecture:i386
Distribution:Debian
Filename:libtorch3-dev_3.1-1.1_i386.deb

/usr/share/doc/libtorch3-dev/examples/decoder/README

README for TODE
---------------

This is the main program for TODE (TOrch DEcoder).

./tode.cc - the main program source

After the executable has been built, a summary of
available options can be displayed by typing

tode -help

A comprehensive user manual can be obtained from
the Torch website (http://www.torch.ch/documentation.php)

For assistance, suggestions, etc. please contact 
Darren Moore
more»

/usr/share/doc/libtorch3-dev/examples/discriminatives/README

---------------------------------------------------

Some examples to learn how to *program* in Torch3.
Of course you can use them without any changes,
but you will not use 1/10 of the library if you
don't want to code something!

boosting.cc:  adaboost with MLP in classification.
knn.cc:       K-nearest-neighbors algorithm.
mlp.cc:       multi-layered perceptron.
svm.cc:       support vector mach
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/usr/share/doc/libtorch3-dev/examples/generatives/README

---------------------------------------------------

Some examples to learn how to *program* in Torch3.
Of course you can use them without any changes,
but you will not use 1/10 of the library if you
don't want to code something!

kmeans.cc  : simple K-means models
gmm.cc     : simple Gaussians Mixtures Models
hmm.cc     : simple Hidden Markov Models (see speech and 
             decoder example f
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/usr/share/doc/libtorch3-dev/examples/speech/README

README: how to use the example mains for speech recognition
-----

Files:

phonemes_*: contain the l
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/usr/share/doc/libtorch3-dev/changelog.Debian.gz

torch3 (3.1-1.1) unstable; urgency=high

  * NMU.
  * libtorch3-dev: Fix libstdc++-dev debpendency.

more»

/usr/share/doc/libtorch3-dev/examples/LICENSE

Copyright (c) 2003--2004 Ronan Collobert
Copyright (c) 2003--2004 Samy Bengio
Copyright (c) 2003--2
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/usr/share/doc/libtorch3-dev/copyright

This package was debianized by Cosimo Alfarano <kalfa@debian.org> on
Thu, 21 Aug 2003 14:50:28 +0200
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