DTSC - 4410 Statistical Learning Models I (3)
A survey of statistical learning models for undergraduate students with a background in statistics, for professional programs in which familiarity with supervised and unsupervised learning is needed. The topics include model selection for regression and classification, tree-based methods, dimension reduction, and clustering analysis. Applications are also discussed as well as computation.
Instructional Method: LD Lecture-Discussion, HL Hybrid Lecture, OL Online Lecture Fall, Spring, Summer Prerequisite:
- STAT 4219: and
- MATH 4240:
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