Undergraduate Fundamentals of Machine Learning

Abstract

Drawing on lectures, course materials, existing textbooks, and other resources, we synthesize and consolidate the content necessary to offer a successful first exposure to machine learning for students with an undergraduate-level background in linear algebra and statistics. The final product is a textbook for Harvard’s introductory course in machine learning, CS 181. This work is motivated by a lack of resources for individuals with an undergraduate background in the areas necessary to succeed in an introductory course in machine learning. Specifically, existing textbooks are too encyclopedic to be expedient for students seeing the material for the first time, or they assume mathematical and statistical maturity beyond that of undergraduates. Like other professors and students have done for several courses at Harvard, we seek to solve this problem with a properly-scoped textbook following the trajectory of the course.