CS 3780
Last Updated
- Schedule of Classes - December 8, 2024 7:33PM EST
- Course Catalog - December 8, 2024 7:07PM EST
Classes
CS 3780
Course Description
Course information provided by the Courses of Study 2024-2025.
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.
Fees Course fee: $30.
Prerequisites/Corequisites Prerequisite: probability theory (e.g. BTRY 3080, CS 2800, ECON 3130, ENGRD 2700, MATH 4710) and linear algebra (e.g. MATH 2210, MATH 2310, MATH 2940), single-variable calculus (e.g. MATH 1110, MATH 1920) and programming proficiency (e.g. CS 2110).
Forbidden Overlaps 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).
Distribution Category (SDS-AS) (OPHLS-AG)
Regular Academic Session. Choose one lecture and one project. Combined with: CS 5780
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Credits and Grading Basis
4 Credits Opt NoAud(Letter or S/U grades (no audit))
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Class Number & Section Details
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Meeting Pattern
- TR
- Jan 21 - May 6, 2025
Instructors
Gangavarapu, T
Sridharan, K
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Additional Information
Instruction Mode: In Person
Enrollment limited to: Computer Science students. All others should add themselves to the waitlist in January during add/drop.
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