Students will learn about the theoretical foundations of machine learning and how to apply machine learning to solve new problems. Machine learning is an exciting and fast-moving field at the intersection of computer science, statistics, and optimization, with many consumer applications such as machine translation, speech recognition, and recommendation. Machine learning also plays an increasingly central role in data science, enabling discoveries in fields such as biology, physics, neuroscience, and medicine. In the first part of the course, students will learn about supervised prediction methods including linear and logistic regression, support vector machines, ensemble methods, and decision trees. In the second part of the course, students will learn about methods for clustering, dimensionality reduction, and statistical inference.
Computer Science (Undergraduate)
4 credits – 15 Weeks
Sections (Spring 2021)
CSCI-UA 473-000 (9300)01/28/2021 – 05/10/2021 Mon,Wed2:00 PM – 3:00 PM (Early afternoon)at Washington SquareInstructed by Wilson, Andrew