CS 3790 Pattern Recognition (ECE 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.

  • Credits: 3

Requirements and Grading

Past Sections

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