CS 4787

CS 4787

Course information provided by the Courses of Study 2020-2021.

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 Spring.

Prerequisites/Corequisites Prerequisite: CS 4780 or CS 5780, CS 2110 or equivalents.

Distribution Category (SMR-AS)

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Enrollment Information
Syllabi: none
  •   Regular Academic Session. 

  • 4 Credits Stdnt Opt

  • 11638CS 4787  LEC 001

    • MWOnline Meeting
    • Feb 8 - May 14, 2021
    • De Sa, C

  • Instruction Mode: Online
    Enrollment limited to CIS students only. All others should add themselves to the waitlist during add/drop. Please see http://www.cs.cornell.edu/courseinfo/enrollment for more information.