Course Description
Pre-Requisite(s):
A prior course in regression and a prior course in programming
Discipline(s):
Quantification, Computation & Data Analysis
This course introduces various topics in machine learning, including regression, classification, resampling methods, linear model selection and regularization, tree-based methods, support vector machines, and unsupervised learning. The statistical software R is incorporated throughout.
