STT 4640 - Machine Learning

Credit Hour(s): 3

Course Description: Statistical models and computational algorithms are used to perform machine learning. Topics include classification and regression trees, bagging and boosting, resampling methods, bootstrapping, regularization, splines, random forest, principal component analysis. Software used for this course includes R.

Prerequisite(s): (Undergraduate level STT 3600 Minimum Grade of B or Graduate level STT 5600 Minimum Grade of B) and (Undergraduate level STT 3610 Minimum Grade of B or Graduate level STT 5610 Minimum Grade of B)

Course Level: Undergraduate
Schedule Type(s): Lecture

Grade Mode: Standard