- Schedule of Classes - September 9, 2021 7:14PM EDT
- Course Catalog - September 9, 2021 7:15PM EDT
Course information provided by the Courses of Study 2020-2021.
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 Spring.
Prerequisites/Corequisites Prerequisite: CS 4780 or CS 5780, CS 2110 or equivalents.
Distribution Category (SMR-AS)
Regular Academic Session.
Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
Class Number & Section Details
- MWOnline Meeting
- Feb 8 - May 14, 2021
De Sa, C
Instruction Mode: Online
Enrollment limited to CIS students only. All others should add themselves to the waitlist during add/drop. Please see http://www.cs.cornell.edu/courseinfo/enrollment for more information.
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