Statistical Learning

Catalog description

This course gives an overview of the main concepts, techniques and algorithms that are relevant for the theory and practice of statistical learning. The course covers the fundamental topics of classification, regression and clustering, starting with simple learning models such as linear regression, decision trees and logistic regression, and ending with more advanced models including Support Vector Machines and neural networks. This course is required the BS in AI major.