Pattern Recognition & Machine Learning

Catalog description

This course covers fundamental concepts, theories, and algorithms for pattern recognition and machine learning. It includes basic ideas on probability and statistics, parametric and non-parametric learning, data clustering, support vector machine, and neural networks. It covers multiple applications, such as pattern recognition in bioinformatics and pattern analysis & machine intelligence in healthcare. Cross-listed: CSC 588