MATH 7636 - Adv Stat Learning II

Credit Hours: (3)

Description This is the second 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 Bayesian methods, EM algorithm, MCMC, additive models, tree based methods, boosting methods, neural networks, support vector machines, discriminant analysis, clustering, PCA, and random forests. PREREQUISITE(S): MATH 7635 OR MATH 8635.