STT 450 - Statistical Machine Learning

Introduction to fundamental principles and applications of machine learning techniques. Topics include linear regression, classification, re-sampling methods, model selection, tree-based classification methods, and Support Vector Machines (SVM). Students learn how to analyze large/high-dimensional real-world application data to build effective machine learning systems using standard programming tools.

Credit Hours: 3

Prerequisite Courses: Any of the following introductory statistics courses (STT 215 or STT 210 or STT 301 or PSY 225 or BAN 280) & any 3-credit 300-level course in STT, MAT, DCS, CSC, and ISE

Crosslisting: Yes
Course Repeatability: Course may not be repeated.