CS 6787

Advanced Machine Learning Systems

Course Description

Course information provided by the 2017-2018 Catalog.

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.

Prerequisites/Corequisites Prerequisite: CS 4780 or CS 4786.

When Offered Fall.

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