PSTAT 231 - Introduction to Statistical Machine Learning

Statistical Machine Learning is used to discover patterns and relationships in large data sets. Topics will include: data exploration, classification and regression trees, random forests, clustering and association rules. Building predictive models focusing on model selection, model comparison and performance evaluation. Emphasis will be on concepts, methods and data analysis; and students are expected to complete a significant class project, individual or team based, using real world data.

Prerequisites: PSTAT 120A-B; and PSTAT 126 with a minimum grade of C or better.

PSTAT 231

20 / 20 Full

Introduction to Statistical Machine Learning

Guo Yu 3.1

T R

11:00 AM - 12:15 PM

77.5% A

PSTAT 231

14 / 20 Enrolled

Introduction to Statistical Machine Learning

Guo Yu 3.1

T R

12:30 PM - 13:45 PM

77.5% A