Go to Main Content

SCT WWW Information System

 

HELP | EXIT

Detailed Course Information

 

Fall 2017 Semester
Nov 23, 2017
Transparent Image
Information Select the desired Level or Schedule Type to find available classes for the course.

DS 5220 - Supervised Machine Learning and Learning Theory
Introduces supervised machine learning, which is the study and design of algorithms that enable computers/machines to learn from experience or data, given examples of data with a known outcome of interest. Offers a broad view of models and algorithms for supervised decision making. Discusses the methodological foundations behind the models and the algorithms, as well as issues of practical implementation and use, and techniques for assessing the performance. Includes a term project involving programming and/or work with real-life data sets. Requires profiency in a programming language such as Python, R, or MATLAB.
4.000 Credit hours
4.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture

Data Science Department

Course Attributes:
Graduate CCIS Data Sci Cert

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

Prerequisites:
Graduate level CS 5800 Minimum Grade of C or Graduate level EECE 7205 Minimum Grade of C

Return to Previous New Search
Transparent Image
Skip to top of page
Release: 8.7.2