CS 4787
Last Updated
- Schedule of Classes - June 25, 2020 7:14PM EDT
- Course Catalog - June 25, 2020 7:15PM EDT
Classes
CS 4787
Course Description
Course information provided by the Courses of Study 2019-2020.
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.
Regular Academic Session.
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Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
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Class Number & Section Details
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Meeting Pattern
- MW Hollister Hall B14
- Jan 21 - May 5, 2020
Instructors
De Sa, C
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Additional Information
Instruction Mode: Hybrid - Online & In Person