- Schedule of Classes - April 13, 2023 2:00PM EDT
- Course Catalog - April 12, 2023 7:14PM EDT
Course information provided by the Courses of Study 2022-2023.
An introduction to the mathematical and algorithms design principles and tradeoffs that underlie large-scale machine learning on big training sets. Topics include: stochastic gradient descent and other scalable optimization methods, mini-batch training, accelerated methods, adaptive learning rates, parallel and distributed training, and quantization and model compression.
When Offered Fall.
Prerequisites/Corequisites Prerequisite: CS 4780 or CS 5780, CS 2110 or equivalents.
Regular Academic Session. Combined with: CS 4787
Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
Class Number & Section Details
- MW Kimball Hall B11
- Aug 22 - Dec 5, 2022
De Sa, C
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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