- Schedule of Classes - January 20, 2022 7:27PM EST
- Course Catalog - January 20, 2022 7:14PM 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).
Distribution Category (SDS-AS)
Regular Academic Session. Combined with: CS 5780
Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
Class Number & Section Details
- MW Statler Hall 185-Aud
- Jan 24 - May 10, 2022
De Sa, C
Instruction Mode: In Person
Enrollment limited to CIS students only. All others should add themselves to the waitlist in January during add/drop.
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