STAT 435

Introduction to Statistical Machine Learning
4.0 credits

Course Description

Introduces the theory and application of statistical machine learning. Topics may include supervised versus unsupervised learning; cross-validation; the bias-variance trade-off; regression and classification; regularization and shrinkage approaches; non-linear approaches; tree-based methods; and support vector machines. Includes applications in R. Course overlaps with: CEE 415. Prerequisite: either STAT 341or STAT 391; recommended: MATH 208. Offered: Sp.

Upcoming Time Schedule

Spring, 2025

SLN/Section Time Location Instructor
20130 A
Open

T Th 11:30AM - 12:50PM

ECE 105

STAT MAJORS ONLY FOR ALL PERIODS. --- PLEASE SUBSCRIBE TO UW NOTIFY IF YOU WOULD LIKE TO GET SEAT ALERTS FROM THE UNIVERSITY. PLEASE CONTINUE TO USE UW NOTIFY BEFORE AND AFTER QUARTER STARTS. --- JOINT WITH STAT 435 B.

 

 

20131 AA
Open

W 2:30PM - 3:20PM

CMU 226

JOINT WITH STAT 435 BA.

 

 

20132 AB
Open

W 3:30PM - 4:20PM

THO 119

JOINT WITH STAT 435 BB.

 

 

20133 B
Open

T Th 11:30AM - 12:50PM

ECE 105

ACMS MAJORS ONLY FOR PERIOD 1. ACMS AND STAT MAJORS ONLY FOR PERIOD 2 AND 3. --- PLEASE SUBSCRIBE TO UW NOTIFY IF YOU WOULD LIKE TO GET SEAT ALERTS FROM THE UNIVERSITY. PLEASE CONTINUE TO USE UW NOTIFY BEFORE AND AFTER QUARTER STARTS. --- JOINT WITH STAT 435 A.

 

 

20134 BA
Open

W 2:30PM - 3:20PM

CMU 226

JOINT WITH STAT 435 AA.

 

 

20135 BB
Open

W 3:30PM - 4:20PM

THO 119

JOINT WITH STAT 435 AB.