Units: 12 units (3-0-9)
Prereqs: 18.02, 6.006 or equivalent; permission of instructors; limited enrollment
Instructors: Professors Regina Barzily (email@example.com), Tommi Jaakkola (firstname.lastname@example.org)
Schedule:WF1-2:30, room 32-044
This subject counts as an Artificial Intelligence subject.
The course focuses on modeling with machine learning methods with an eye towards applications in engineering and sciences. Students will be introduced to modern machine learning methods, from supervised to unsupervised models, with an emphasis on newer neural approaches. The course focuses on the understanding of how and why the methods work from the point of view of modeling, and when they are applicable. Using concrete examples, the course covers formulation of machine learning tasks, adapting and extending methods to given problems, and how the methods can and should be evaluated.