Course Catalog

INFS6482 - Machine Learning

Fall 2022

This course will cover the theory and practical application of machine learning algorithms. Students in this course will study supervised and unsupervised learning algorithms. Students will apply machine learning algorithms to datasets to uncover patterns using R and Python. Topics covered include: cluster analysis and association rules, generalized linear models, bagging, kernel methods, random forest, support vector machines, neural networks, k-nearest neighbor, among other algorithms.
Prerequisite -- CI555.
3 Credits

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 M  Monday
 T  Tuesday
 W  Wednesday
 R  Thursday
 F  Friday
 S  Saturday
 U  Sunday

Schedule Book for All Active and Available Future Terms, Course starting with INFS6482
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Credits: 3
Location: Internet/ Online
Time: -
Instructor: Stewart
Session: 4 (10/22 - 12/16/22)
Term: Fall 2022
Prerequisite -- CI555.
Course is taught Fully Online.