This course presents a variety of computational tools for modeling and understanding complex data. Topics include manipulating data, exploratory data analysis, statistical inference, spam filters and naive Bayes, neural networks, and machine learning algorithms such as linear regression, k-nearest neighbors, and k-means. The course will focus on both understanding the mathematics underlying the computational methods and gaining hands-on experience in the application of these techniques to real datasets.
Prerequisites
MAT 140, MAT 258