MATH480-01A Special Topics: Intro to Statistical Machine Learning (with Kourosh Zarringhalam)
This special topics course will provide an introduction to methods in statistical machine learning that are commonly used to extract important patterns and information from data. Topics include: supervised and unsupervised learning algorithms such as generalized linear models for regression and classification, support vector machines, random forests, k-means clustering, principal component analysis, and the basics of neural networks. Model selection, cross-validation, regularization, and statistical model assessment will also be discussed. The topics and their applications will be illustrated using the statistical programing language R in a practical, example/project oriented manner.
Registration for Summer Session I is closed.