This course aims at providing mathematical explanations of the machine learning models discussed in DSC 105 and DSC 205. Topics include probability, probabilistic models, statistical concepts related to machine learning, and analysis of some of the popular machine learning models with the help of probability and statistics. Projects will reflect real world challenges and will aim at discovering how machine learning models work.
Prerequisites
DSC 105, DSC 205, CSC 265, or permission of the instructor.