CS 456 Mathematical Foundations of Machine Learning
This course will give students a rigorous introduction to the mathematical foundations of machine learning, including but not limited to frequently used tools in linear algebra, calculus, probability, and widely applied methods such as linear regression and logistic regression/support vector machines. In addition, this course provides hands-on training on implementing these algorithms via python from scratch and using libraries such as numpy, scipy, sklearn and matplotlib.
Distribution
School of Engineering and Science