CS 4780

CS 4780

Course information provided by the Courses of Study 2021-2022.

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.

When Offered Fall, Spring.

Prerequisites/Corequisites Prerequisite: probability theory (e.g. BTRY 3080, ECON 3130, MATH 4710, ENGRD 2700) and linear algebra (e.g. MATH 2940) and calculus (e.g. MATH 1920) and programming proficiency (e.g. CS 2110).

Distribution Category (SDS-AS)

View Enrollment Information

  •   Regular Academic Session.  Combined with: CS 5780

  • 4 Credits Stdnt Opt

  • 10844 CS 4780   LEC 001

  • Instruction Mode: In Person
    Enrollment limited to CIS students only. All others should add themselves to the waitlist in January during add/drop.