CS 5780

CS 5780

Course information provided by the Courses of Study 2024-2025.

The course provides an introduction to machine learning, focusing on supervised learning and its theoretical foundations. Topics include regularized linear models, boosting, kernels, deep networks, generative models, online learning, and ethical questions arising in ML applications.

When Offered Fall, Spring.

Fees Course fee: $30.
Prerequisites/Corequisites Prerequisite: CS 2800, probability theory (e.g. BTRY 3080, ECON 3130, MATH 4710, ENGRD 2700) and linear algebra (e.g. MATH 2940), calculus (e.g. MATH 1920) and programming proficiency (e.g. CS 2110).

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one project. Combined with: CS 3780

  • 4 Credits Opt NoAud

  •  7392 CS 5780   LEC 001

    • TR
    • Jan 21 - May 6, 2025
    • Gangavarapu, T

      Sridharan, K

  • Instruction Mode: In Person
    Enrollment limited to: Master of Engineering (M.Eng.), Computer Science (CS) students, and Computer Science Early Admit students.
    For Bowers Computer and Information Science (CIS) Course Enrollment Help, please see: https://tdx.cornell.edu/TDClient/193/Portal/Home/

  •  8765 CS 5780   PRJ 601

    • TBA
    • Jan 21 - May 6, 2025
    • Gangavarapu, T

      Sridharan, K

  • Instruction Mode: In Person