CSI 6160 - Machine Learning

(4 credits)

Introduction to recognition and learning; Bayes decision theory; parametric and nonparametric methods including Hidden Markov models; Discriminant functions including support vector machines; Multilayer neural networks; Decision and regression trees for learning; Performance estimation; Unsupervised learning and clustering; Subspace methods; Application. This course requires backgrounds on data structures and algorithms. Formerly, CSE 616.

Course revisions made after the Graduate Catalog publication date will be posted in the Graduate Catalog Addendum.