CS 6787
Last Updated
- Schedule of Classes - January 9, 2020 9:13AM EST
- Course Catalog - January 9, 2020 9:14AM EST
Classes
CS 6787
Course Description
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.
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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 Upson Hall 142
Instructors
De Sa, C
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