MATH 7635 - Adv Stat Learning I

Credit Hours: (3)

Description This is the first course in a two-course sequence designed to introduce students to a set of tools used in the modeling and understanding of big data at a more advanced level. The two-part course introduces statistical methods in the context of developments in computer science. Emphasis is on application to real data sets. Topics include linear regression, shrinkage methods, linear discriminant analysis, logistic regression, nonparametric logistic regression, kernel methods, cross validation and bootstrap methods. PREREQUISITE(S): MATH 4635/6635 and MATH 4636/6636.