Artificial Intelligence
Artificial Intelligence :
The use of programs to enable machines to perform tasks which humans perform using their intelligence. Early AI avoided human pychological models, but this orientation has been altered by the development of connectionism, which is based on theories of how the brain works. In connectionism, complex functions, including learning, involve the transmission of information along pathways formed among large arrays of simple elements
From: www.filosofia.net/materiales/rec/glosaen.htm
Torch
It's a machine-learning library, written in simple C++ and distributed now under a BSD license.
Features
A lot of things in gradient machines, that is, machines which could be learned with a gradient descent. This includes multi-layered perceptrons, radial basis 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).
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Torch
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