- Schedule of Classes - January 8, 2020 7:14PM EST
- Course Catalog - January 8, 2020 7:15PM EST
Course information provided by the Courses of Study 2019-2020.
Graduate-level introduction to system-focused aspects of machine learning, covering guiding principles and commonly used techniques for scaling up to large data sets. Topics will include stochastic gradient descent, acceleration, variance reduction, methods for choosing metaparameters, parallelization within a chip and across a cluster, and innovations in hardware architectures. An open-ended project in which students apply these techniques is a major part of the course.
When Offered Fall.
Prerequisites/Corequisites Prerequisite: CS 4780 or CS 4786.
Regular Academic Session.
Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
Class Number & Section Details
- MWUpson Hall 142
De Sa, C
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