|
Dec 26, 2024
|
|
|
|
CSE 616 - Pattern Recognition and Machine Learning (4 credits)
Introduction to recognition and learning; Bayes decision theory; parametric and nonparametric methods including Hidden Markov models; Discriminant functions including support vector machines; Multilayer neural networks; Decision and regression trees for learning; Performance estimation; Unsupervised learning and clustering; Subspace methods; Application.
Prerequisite(s): Students must meet prerequisites (CSE 506 and CSE 507 or equivalent).
Add to Portfolio (opens a new window)
|
|