STAT5211 — Statistical Learning
Theoretical foundations and applications of machine learning models. Supervised and unsupervised learning methods are covered, including linear regression, classification, nonparametric regression, tree-based methods, classification methods, and principal component analysis. Resampling methods for assessing goodness-of-fit and subset selection procedures are also considered. Prerequisites: STAT 3612, (MATH 3280 or MATH 3326 or MATH 4326) or graduate student.