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

DS 5230 - Unsupervised Machine Learning and Data Mining
Introduces unsupervised machine learning and data mining, which is the process of discovering and summarizing patterns from large amounts of data, without examples of data with a known outcome of interest. Offers a broad view of models and algorithms for unsupervised data exploration. 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

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