Machine Learning I

Taught by Pamela Schlosser

Course description:

This course is designed to provide students with a deep understanding of the theory and practive of regression and classification, two of the most commonly used techniques in the data scientist’s toolkit. These predictive analytics techniques are important members of a family of analytics often referred to as machine learning techniques, and they are the basis for more elaborate machine learning techniques that will be covered in a sequential course called Machine Learning II. An important part of this course will cover a powerful and ubiquitous software package called R, whic his used extensively in labs and assignments in this class and subsequently reappears in other classes throughout the program.