CSE 4309
Introduction to Machine Learning

Fall 2017
Lectures: MW 1:00pm-2:20pm
Room: NH 112
Instructor: Vassilis Athitsos

This course offers an introduction to machine learning. Topics include naive Bayes classifiers, linear regression, linear classificiers, neural networks and backpropagation, kernel methods, decision trees, clustering, and reinforcement learning. A strong programming background is assumed, as well as familiarity with linear algebra (vector and matrix operations), and knowledge of basic probability theory and statistics. Prerequisite: Admitted into an Engineering Professional Program. C or better in each of the following: CSE 2320, IE 3301 and CSE 3380 or MATH 3330.