CS 6780

Course information provided by the Courses of Study 2014-2015.

Gives a graduate-level introduction to machine learning and statistical pattern recognition 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, such as data mining, computer vision, robotics, text and web data processing. An open research project is a major part of the course.

When Offered Spring.

Permission Note Enrollment limited to: PhD students, or by permission of instructor.
Prerequisites/Corequisites Prerequisites: 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).

Comments Students who have already taken CS 4780/CS 5780 should not take this class.

View Enrollment Information

Enrollment Information
Syllabi: none
  •   Combined with: CS 6780

  • 4 Credits Stdnt Opt

  • 16868CS 6780  LEC 001

  •  
  • Enrollment limited to: PhD students.

Enrollment Information
Syllabi: none
  •   Combined with: CS 6780

  • 4 Credits Stdnt Opt

  • 16869CS 6780  LEC 002

  •  
  • Enrollment limited to: students enrolled at the Cornell Tech campus. Offered in NYC via distance learning.