STAT 452 - Introduction to Statistical Learning

Units: 3
Introduction to statistical machine learning. Supervised learning including linear regression, logistic regression, and classification methods. Unsupervised learning including clustering. Re-sampling methods such as random forests, cross-validation, boosting, and bagging. Applications to data mining, statistical pattern recognition, and data processing.

Prerequisites: One of: STAT 110, STAT 303, STAT 310, STAT 315, STAT 330.
Equivalent Quarter Course: STAT 4869.
Possible Instructional Methods: Entirely On-ground.
Grading: A-F or CR/NC (student choice).
Course Typically Offered: Spring ONLY