- Schedule of Classes - November 25, 2021 7:40PM EST
- Course Catalog - November 25, 2021 7:27PM EST
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).
Regular Academic Session. Combined with: CS 4780
Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
Class Number & Section Details
- TR Statler Hall 185-Aud
- Aug 26 - Dec 7, 2021
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
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