Courses of Study 2016-2017 
    Oct 27, 2021  
Courses of Study 2016-2017 [ARCHIVED CATALOG]

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CS 4786 - Machine Learning for Data Science

Fall. 4 credits.

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 .


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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