Electrical and Comp Engineerng
EECE 5644: Introduction to Machine Learning and Pattern Recognition
Lecture - 4 credits
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- Studies machine learning (the study and design of algorithms that enable computers/machines to learn from experience/data).
- Covers a range of algorithms, focusing on the underlying models between each approach.
- Emphasizes the foundations to prepare students for research in machine learning.
- Topics include Bayes decision theory, maximum likelihood parameter estimation, model selection, mixture density estimation, support vector machines, neural networks, probabilistic graphics models, and ensemble methods (boosting and bagging).
- Offers students an opportunity to learn where and how to apply machine learning algorithms and why they work.
Studies machine learning (the study and design of algorithms that enable computers/machines to learn from experience/data). Show more.
Pre-requisites