- Schedule of Classes - June 15, 2016 6:14PM EDT
- Course Catalog - June 9, 2016 6:15PM EDT
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.
Combined with: CS 4786
Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
Class Number & Section Details
- TRPhillips Hall 101
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.
Disabled for this roster.