2025 Fall > GRAD > MATH > MATH 655
An Introduction to Statistical Machine Learning
Course #: MATH 655
Description:
This course will provide an introduction to methods in statistical machine learning that are commonly used to extract important patterns and information from data. Topics include: supervised and unsupervised learning algorithms such as generalized linear models for regression and classification, support vector machines, random forests, k-means clustering, principal component analysis, and the basics of neural networks. Model selection, cross-validation, regularization, and statistical model assessment will also be discussed. The topics and their applications will be illustrated using the statistical programming language R in a practical, example/project oriented manner.
| Section | Class Number | Schedule/Time | Instructor | Location | |
|---|---|---|---|---|---|
| 01 | 3560 | TuTh 5:30 - 6:45 pm |
, | McCormack M03-0617 | |
|
Session:
Regular
Class Dates:
09/02/2025 - 12/12/2025
Capacity:
5
Enrolled:
0
Status:
Open
Credits:
4/4
Class Notes:
Pre Requisites:
Course Attributes:
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