COSC 522 - Machine Learning

3 Credit Hours

Theoretical and practical aspects of machine learning techniques related to pattern recognition. Statistical methods studied include Bayesian and linear classifiers, support vector machines, neural networks, and unsupervised learning. Syntactic methods include grammatical inference, string matching and Markov chains. Ensemble methods include random forests, adaptive boosting, and classifier fusion.
Recommended Background: Programming, probability theory, linear algebra.

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