CS 6787

CS 6787

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

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.

View Enrollment Information

Enrollment Information
Syllabi: none
  •   Regular Academic Session. 

  • 4 Credits Stdnt Opt

  • 11234CS 6787  LEC 001

  • Instruction Mode: In Person Transition to Online
    Enrollment is restricted to grad students only. Undergraduates will need to add themselves to the waitlist during add/drop.
    Enrollment limited to students who are able to attend in-person classes in the Ithaca area.
    Enrollment limited to students who are able to attend in-person classes in the Ithaca area.

Enrollment Information
Syllabi: none
  •   Regular Academic Session. 

  • 4 Credits Stdnt Opt

  • 20095CS 6787  LEC 002

    • MWOnline Meeting
    • Sep 2 - Dec 16, 2020
    • De Sa, C

  • Instruction Mode: Online
    Enrollment is restricted to grad students only. Undergraduates will need to add themselves to the waitlist during add/drop.