ECGR 4105 - Introduction to Machine Learning

Machine learning is a sub-field of Artificial Intelligence that gives computers the ability to learn and/or act without being explicitly programmed. This course examines the necessary theory, principles and algorithms for machine learning.  Topics include: supervised, unsupervised learning approaches (including deep learning), optimization procedures, and statistical inference.  Students digest and practice their knowledge and skills by class discussion, homework, and exams, as well as obtain in-depth experience with a particular topic through a final project.  To prepare students to be successful in this course, light reviews on linear algebra and matrix analysis and programming tutorials are provided as additional course reading materials.

Credit Hours: (3)
Prerequisite(s): ECGR 3101  or ECGR 3111  
Cross-listed Course(s): ECGR 5105
Most Recently Offered (Day): Fall 2021
Most Recently Offered (Evening): Course has not been offered at this time in the past 3 years

Schedule of Classes