CS 5786

Last Updated

  • Schedule of Classes - June 15, 2016 6:14PM EDT
  • Course Catalog - June 9, 2016 6:15PM EDT

CS 5786
Machine Learning for Data Science

Course information provided by the Courses of Study 2015-2016.

An introduction to machine learning for data-science applications. Topics include dimensionality-reduction (such as principal components analysis, canonical correlation analysis, and random projection); clustering (such as k-means and single-link); probabilistic modeling (such as mixture models and the EM algorithm). This course can be taken independently or in any order with CS 4780/CS 5780.

When Offered Spring.

Prerequisites/Corequisites Prerequisite: Probability theory (BTRY 3080, ECON 3130, MATH 4710, or strong performance in ENGRD 2700 or equivalent); linear algebra (strong performance in MATH 2940 or equivalent); CS 2110 or equivalent programming proficiency.

View Enrollment Information

Syllabi: none

  •   Regular Academic Session.  Combined with: CS 4786

  • 4 Credits Stdnt Opt

  • 12432 CS 5786   LEC 001

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  • Enrollment open only to CIS graduate students. (Undergraduate CIS students should enroll in CS 4786.) All others should add themselves to the waitlist. Please go to http://www.cs.cornell.edu/courseinfo/enrollment for updates.