MATH 462 - Mathematics of Machine Learning

Machine learning is a rapidly growing field that is concerned with finding patterns in data. It is responsible for tremendous advances in technology, from personalized product recommendations to speech recognition in cell phones. This course material covers theoretical foundations, algorithms, and methodologies for machine learning, emphasizing the role of probability and optimization and exploring a variety of real-world applications. Through lecture examples and programming projects, students will learn how to apply powerful machine learning techniques to new problems. Students are expected to have a solid foundation in calculus and linear algebra as well as exposure to the basic tools of logic and probability, and should be familiar with at least one modern, high-level programming language.
Units: 4
Course Type: Seminar