Detailed Course Information |
Fall 2022
May 16, 2025 |
|
 |
||
| CMPS 460 - Machine Learning |
|
Fundamental principles of machine learning, supervised learning, unsupervised learning, instance-based learning, decision tree induction, Bayesian inference, support vector machines, multi-layer neural networks, and performance evaluation of machine learning algorithms. Hands-on experience with implementing machine learning applications.
3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Computer Science & Engineering Department Course Attributes: Engineering Course (TUI) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: Undergraduate level GENG 200 Minimum Grade of D and Undergraduate level CMPS 303 Minimum Grade of D |
| Return to Previous | New Search |
|