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| CSC 322 - Data & Machine Learning |
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Concepts/techniques in machine learning and multidisciplinary applications. Topics include data cleaning/transformation; data visualization; association/correlation rules; data classification and predictive modeling (such as SVMs); performance analysis and scalability; data mining with tabular, multi-dimensional and unstructured data, including text, audio, images; big-data frameworks (such as Spark, Hadoop, HIVE, Pig); and emerging themes and challenges.
3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Computer Science Department Restrictions: May not be assigned one of the following Student Attributes: Online Accelerated Programs Prerequisites: (Undergraduate level CSC 231 Minimum Grade of D- or Undergraduate level ISE 221 Minimum Grade of D-) and Undergraduate level MAT 161 Minimum Grade of D- |
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