CSE 4309/6363/6364
Machine Learning

Spring 2020
Lectures: MWF 10:00am-10:50am
Room: ERB 129
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. Prerequisites for CSE 4309: Admitted into an Engineering Professional Program, and C or better in each of the following: CSE 2320, IE 3301 and CSE 3380 or MATH 3330. Prerequisites for CSE 6363 and 6364: Grade of C or better in CSE 5301.