STT 6640 - Machine Learning

Credit Hour(s): 3

Course Description: Classification. Resampling methods including bootstrapping. Regularization. Splines. Classification and regression trees. Bagging and boosting. Random forest. Unsupervised learning including principal component analysis. Software used for this course includes R.

Prerequisite(s): Graduate level STT 5600 Minimum Grade of C and Graduate level STT 5610 Minimum Grade of C

Enrollment Restrictions: Must be enrolled in one of the following levels: Graduate, Medical, Professional.

Course Level: Graduate
Schedule Type(s): Lecture

Grade Mode: Standard
Term(s) Offered: Fall, Spring, Summer