DAT 4380: Introduction to Machine Learning (2023-2024)

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An introduction to statistical machine learning. Emphasis on applications and practical implementation of machine learning algorithms using the R programming language, with a conceptual overview of the underlying theory and mathematics. Topics include a variety of supervised learning methods for regression and classification as well as unsupervised learning methods for clustering and dimension reduction. Also explores ethical and societal issues that arise in applications of machine learning. Typically offered: Occasionally.

Term CRN Credits Instructor(s) Days Time Dates Location Open
Winter 21699 5 Brian Gill
Arranged
W
-
9:00AM-10:20 AM
01/03-03/14
01/03-03/14
**Online
Otto Miller Hall 139
-
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Attributes: Upper-Division
Grade Modes: (Default) Normal Grading
Instructional Methods: Blended
Note: Full Term

Prerequisites:
(MAT 3380: C- or better
OR DAT 3380: C- or better)
AND (MAT 3333: C- or better
OR BUS 3700: C- or better
OR BIO 4360: C- or better
OR PSY 4428: C- or better)