Mathematics of Artificial Intelligence II

Catalog description

This course covers the fundamental mathematical tools needed to understand Machine Learning (ML). A core set of Machine Learning (ML) topics are covered, which could include multivariate regression techniques, principal component analysis (PCA), tree-based methods, and support vector machines (SVM). An introduction to modern Deep Learning (DL) concepts is provided. With a solid understanding of mathematics in core concepts, students should be able to implement and understand Machine Learning (ML) techniques covered as well as understand the fundamentals of more complex Machine Learning (ML) algorithms. CS 447 is cross-listed with MS 447 , and only one course can be taken for credit.