EEE 4773
Fundamentals of Machine Learning
Overview of machine intelligence and the role of machine learning in a variety of real-world problems. Probability and statistics to handle uncertain data. Topics covered include: learning models from data in both a supervised and unsupervised fashion, linear models and non- linear models for classification, and linear dimensionality reduction.
Topics
- learning models from data in both a supervised and unsupervised fashion
- linear models and non- linear models for classification
- and linear dimensionality reduction
Topics explicitly listed in official catalogue description
Prerequisites & course information
Grading Scheme: Letter Grade Prerequisite: EEL 3135 and EEL 3850 with minimum grades of C. Attributes: Artificial Intelligence
Sources
- Course catalogue ↗2025-2026
- Catalogue entry ↗
Catalogue variants
- Fundamentals of Machine Learning · 3 Credits