CS 4787
Last Updated
- Schedule of Classes - January 11, 2024 7:32PM EST
- Course Catalog - January 11, 2024 7:07PM EST
Classes
CS 4787
Course Description
Course information provided by the Courses of Study 2023-2024. Courses of Study 2023-2024 is scheduled to publish mid-June.
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.
Distribution Category (SMR-AS)
Regular Academic Session. Choose one lecture and one project. Combined with: CS 5777
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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 Phillips Hall 101
- Aug 21 - Dec 4, 2023
Instructors
De Sa, C
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Additional Information
Instruction Mode: In Person
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