Detailed Course Information |
Fall 2018 Semester
May 21, 2019 |
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| DS 5230 - Unsupervised Machine Learning and Data Mining |
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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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