- Schedule of Classes - October 5, 2022 7:29PM EDT
- Course Catalog - October 5, 2022 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.
Distribution Category (SMR-AS)
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