CS 5780

CS 5780

Course information provided by the Courses of Study 2022-2023.

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).

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Combined with: CS 4780

  • 4 Credits Stdnt Opt

  •  9793 CS 5780   LEC 001

    • TR Bailey Hall 101
    • Aug 22 - Dec 5, 2022
    • Damle, A

      Sun, W

  • Instruction Mode: In Person
    Direct enrollment is restricted to CS PhD, MS and MEng students. Seniors taking courses for M.Eng credit and all other graduate and professional students must add themselves to the waitlist during add/drop. Undergraduates who are not taking M.Eng credit will not be permitted and must enroll/waitlist for the 4xxx version. See website for details: http://www.cs.cornell.edu/courseinfo/enrollment/cs-4000-5000-level-courses