CS 6780

CS 6780

Course information provided by the Courses of Study 2023-2024.

Gives a graduate-level introduction to machine learning and in-depth coverage of new and advanced methods in machine learning, as well as their underlying theory. Emphasizes approaches with practical relevance and discusses a number of recent applications of machine learning in areas like information retrieval, recommender systems, data mining, computer vision, natural language processing and robotics. An open research project is a major part of the course. 

When Offered Fall.

Permission Note Enrollment limited to: Ph.D. students or permission of instructor.
Prerequisites/Corequisites Prerequisite: programming skills (at the level of CS 2110) and basic knowledge of linear algebra (at the level of MATH 2940) and probability theory (at the level of MATH 4710) and multivariable calculus (at the level of MATH 1920).

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one project.

  • 4 Credits Stdnt Opt

  • 19167 CS 6780   LEC 001

  • Instruction Mode: In Person
    Restricted to Ithaca campus graduate students only. Undergraduate and MEng students must add themselves to the waitlist during add/drop. This course is not available to Cornell Tech students.

  • 19168 CS 6780   PRJ 601

    • TBA
    • Aug 21 - Dec 4, 2023
    • Joachims, T

  • Instruction Mode: In Person

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one project.

  • 4 Credits Stdnt Opt

  • 20773 CS 6780   LEC 030

  • Instruction Mode: Distance Learning-Synchronous
    Taught in NYC at Cornell Tech. Streamed from Ithaca. Enrollment Limited to Cornell Tech PhD Students Only.

  • 20986 CS 6780   PRJ 630

    • TBA Cornell Tech
    • Aug 21 - Dec 4, 2023
    • Joachims, T

  • Instruction Mode: Distance Learning-Synchronous
    Taught in NYC at Cornell Tech. Streamed from Ithaca. Enrollment Limited to Cornell Tech PhD Students Only.