Founded in 1966

CS 3790: Pattern Recognition (EE 2372)

Description

Emphasis on machine pattern recognition and learning: Bayes decision theory, parameter estimation, Bayesian belief networks, discriminant functions, supervised learning, nonparametric techniques, feature extraction, principal component analysis, hidden Markov models, expectation-maximization, support vector machines, artificial neural networks, unsupervised learning, clustering, and syntactic pattern recognition.

Prerequisites

None.

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