This course is the first of two courses that will introduce students to the exciting and growing literature in machine learning / AI with a focus on applications in finance and marketing. We will cover topics such as regularization, tree methods, bagging/boosting, support vector machines and recommendation algorithms. In the process, we will review several real-world applications drawn from the areas of finance and marketing. Students are expected to be familiar with basic probability theory, linear algebra, and multiple linear regression. Some familiarity with (and willingness to learn) programming is a prerequisite as we will make extensive use of the programming language R.
Adjunct Professor of Business