Machine Learning

Catalog description

Introduction to machine and statistical learning techniques. Topics include supervised learning (regression models, kernel smoothers), unsupervised learning (clustering or principal component analysis), shrinkage models, additive models, and neural networks. P: MTH 360 or MTH 361 or another introductory statistics course with Instructor Consent; DSC 365 .