Introduction to Machine Learning

An introductory course in machine learning covering linear regression, maximum likelihood estimation, and classification methods such as logistic regression, naive Bayes, and support vector machines. Students also practice clustering, data visualization, and dimensionality reduction with principal components analysis, ending with a first treatment of neural networks and deep learning.