DSCI 415 - Unsupervised Learning

(3 credits)

An introduction to machine or statistical learning techniques for finding structure in large complex data. Unsupervised learning methods such as clustering, association rules, text mining, recommender systems and dimension reduction methods will be discussed. Prerequisites: MATH 222 - Data-Driven Mathematical Modeling or MATH 311 - Linear Algebra; and ◆ DSCI 325 - Management of Structured Data; or instructor permission. Grade or P/NC. Offered fall semester alternate years.

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