CS 4786

Last Updated

  • Schedule of Classes - June 25, 2020 7:14PM EDT
  • Course Catalog - June 25, 2020 7:15PM EDT

CS 4786
Machine Learning for Data Science

Course information provided by the Courses of Study 2019-2020.

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). 

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 4780; CS 2110 or equivalent programming proficiency.

View Enrollment Information

Syllabi: none

  •   Regular Academic Session.  Combined with: CS 5786

  • 4 Credits Stdnt Opt

  • 12445 CS 4786   LEC 001

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  • Instruction Mode: Hybrid - Online & In Person
    Enrollment limited to CIS students only. All others may add themselves to the waitlist during add/drop. Please go to http://www.cs.cornell.edu/courseinfo/enrollment for updates. It is expected that undergraduate students enroll in the 4000-level section of this class and graduate students enroll in the 5000-level section of this class.