CS 6787
Last Updated
- Schedule of Classes - November 13, 2024 8:41AM EST
- Course Catalog - November 12, 2024 10:26AM EST
Classes
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CS 6787
Course Description
Course information provided by the 2023-2024 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 Spring.
Regular Academic Session. Choose one lecture and one project.
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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
- Jan 22 - May 7, 2024
Instructors
De Sa, C
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Additional Information
Instruction Mode: In Person
Enrollment is restricted to graduate students only. All others must add themselves to the waitlist during add/drop in January.
Regular Academic Session. Choose one lecture and one project.
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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
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MW
Bloomberg Center 91
Cornell Tech - Jan 22 - May 7, 2024
Instructors
De Sa, C
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MW
Bloomberg Center 91
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Additional Information
Instruction Mode: Distance Learning-Synchronous
Taught in NYC at Cornell Tech. Enrollment Limited to Cornell Tech PhD Students only.
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Class Number & Section Details
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Meeting Pattern
- TBA Cornell Tech
- Jan 22 - May 7, 2024
Instructors
De Sa, C
-
Additional Information
Instruction Mode: Distance Learning-Synchronous
Taught in NYC at Cornell Tech. Enrollment Limited to Cornell Tech PhD Students only.
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