CS 5780 - Introduction to Machine Learning

Fall, Spring. 4 credits. Student option grading (no audit).

Forbidden Overlap: due to an overlap in content, students will not receive credit for both CS 3780 (and the former) CS 4780/5780, ECE 3200 (and the former ECE 4200), ORIE 3741 (and the former ORIE 4741/5741), STSCI 3740 (and the former STSCI 4740/5740).
Prerequisite: CS 2800, probability theory (e.g. BTRY 3080, ECON 3130, MATH 4710, ENGRD 2700), linear algebra (e.g. MATH 2940), calculus (e.g. MATH 1920), and programming proficiency (e.g. CS 2110). Course fee: $30. Co-meets with CS 3780.

Fall: A. Damle, W. Sun; Spring: K. Weinberger.

The course provides an introduction to machine learning, focusing on supervised learning and its theoretical foundations. Topics include: regularized linear models, boosting, kernels, deep networks, generative models, online learning, and ethical questions arising in ML applications.