EESC6364 - Machine Learning and Pattern Recognition

EESC 6364 Machine Learning and Pattern Recognition (3 semester credit hours) This course covers basic concepts and algorithms for pattern recognition and machine learning. Bayesian decision theory, parametric learning, non-parametric learning, linear regression, linear classifiers and support vector machine, kernel methods, data clustering, mixture models, component analysis, multilayer neural networks, deep learning with convolutional neural networks. Prerequisites: Knowledge of probability and knowledge of MATLAB or C. (3-0) T