Statistical Machine Learning 1.

Catalog description

PR: STAT 312 and (PR or CONC: DSCI 222 and MATH 441 ) with a minimum grade of C-. Focuses on a conceptual understanding of statistical machine learning methods and their implementation using python. Covers linear regression; classification methods (logistic regression, linear discriminant analysis, Naive Bayes and K-nearest neighbors); Generalized Linear Models; resampling methods (cross-validation and bootstrap); model choice methods (subset and stepwise selection, shrinkage methods, dimensionality reduction).