CS 5777

CS 5777

Course information provided by the 2025-2026 Catalog.

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.


Last 3 terms offered 2023FA, 2022FA

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Combined with: CS 4787

  • 4 Credits Opt NoAud

  • 19539 CS 5777   LEC 001

    • MW
    • Aug 25 - Dec 8, 2025
    • De Sa, C

  • Instruction Mode: In Person

    For Bowers Computer and Information Science (CIS) Course Enrollment Help, please see: https://tdx.cornell.edu/TDClient/193/Portal/Home/