Computer Science and Engineering

CSE 142 Machine Learning

Introduction to machine learning algorithms and their applications. Topics include classification learning, density estimation and Bayesian learning regression, and online learning. Provides introduction to standard learning methods such as neural networks, decision trees, boosting, and nearest neighbor techniques. (Formerly CMPS 142.)

Requirements

Prerequisite(s): CSE 101; and AM 30, or MATH 22, or MATH 23A; and STAT 131 or CSE 107.

Credits

5

Quarter offered

Fall, Winter, Spring

Instructor

Manfred Warmuth, David Helmbold, Snigdha Chaturvedi, Yang Liu, Xin "Eric" Wang, Evangelos Chatzisfratis