INFS6482-A Machine Learning (Fall 2022)
Course Details
Section will be taught totally online with no scheduled class meetings. Students must arrange for daily access to a computer and the Internet prior to the start of classes. Robert Morris labs are to be used only as a backup in special situations and may not be relied upon for extended periods of time. In addition to the Internet link, online classes have a large emphasis on email. All messages from the instructor and other information regarding online classes, including user ids, passwords, and login instructions will be sent to your Robert Morris University email account. Visit http://rmu.blackboard.com/ for more information.
Session, Dates: 4 (10/22/2022 - 12/16/2022)
Days: ONLINE
Time: -
Location: Internet/Online
Room:
Seats Available: 8 Seats
Credits: 3
Course Description
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.
Prerequisite -- CI555.
Course Materials
Visit the Bookstore. Click for required materials for this course.About the Instructor(s)
John C. Stewart, Ph.D.
stewartj@rmu.edu
412-397-6442 phone
412-397-6469 fax
Wheatley Center 326
Profile
Professor of Computer and Information Systems
Computer and Information Systems
stewartj@rmu.edu
412-397-6442 phone
412-397-6469 fax
Wheatley Center 326
Profile