MACHINE LEARNING

Catalog description

This course introduces the fundamentals and principles of Machine Learning, including supervised learning algorithms such as linear and logistic regression, Gaussian discriminant analysis, naive Bayes classifiers, support vector machines, and neural networks, as well as unsupervised algorithms such as k-means, and expectation maximization.