2023 Fall > UGRD > math > math 455
An Introduction to Statistical Machine Learning
Course #: math 455
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.
Pre Requisites:
Pre-requisite: MATH 345 and MATH 260 and CS 110 or permission of instructor
Section | Class Number | Schedule/Time | Instructor | Location | |
---|---|---|---|---|---|
01 | 4011 | TuTh 4:00 - 5:15 pm |
Zarringhalam,Kourosh | McCormack M02-0213 | |
Session:
Regular
Class Dates:
09/05/2023 - 12/13/2023
Capacity:
15
Enrolled:
1
Status:
Open
Credits:
3/3
Class Notes:
Pre Requisites:
Pre-requisite: MATH 345 and MATH 260 and CS 110 or permission of instructor
Course Attributes:
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