Course: STAT 27725=STAT 25400
Title: Machine Learning
Instructor(s): Yuxin Chen
Teaching Assistant(s): TBD
Class Schedule: Section 1: TR 9:40 AM-11:00 AM (Remote)
Description: This course offers a practical, problem-centered introduction to machine learning. Topics covered include the Perceptron and other online algorithms; boosting; graphical models and message passing; dimensionality reduction and manifold learning; SVMs and other kernel methods; artificial neural networks; and a short introduction to statistical learning theory. Weekly programming assignments give students the opportunity to try out each learning algorithm on real world datasets.
Prerequisite(s): CMSC 15400 or CMSC 12300. STAT 22000 or STAT 23400 strongly recommended.