description
- Consists of applications and methods of statistical learning. Reviews multiple linear regression and then covers classification, regularization, splines, tree-based methods, support vector machines, unsupervised learning and Gaussian process regression. Recommended prerequisite: previous coursework equivalent to that of STAT 3400 or STAT 4010 or STAT 5010; minimum C- grade for all. Same as STAT 4610.