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Cornell University    
 
    
 
  Nov 22, 2017
 
Courses of Study 2017-2018
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CS 4786 - Machine Learning for Data Science


     
Fall. 4 credits. Student option grading.

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. Co-meets with CS 5786 .

Staff.

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 .



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