MIT Subject Listing & Schedule
IAP/Spring 2021 Search Results

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1 subject found.

6.862 Applied Machine Learning

(, )
Prereq: Permission of instructor
Units: 4-0-8
Credit cannot also be received for 6.036
https://eecs.scripts.mit.edu/eduportal/__How_Courses_Will_Be_Taught_Online_or_Oncampus__/S/2021/#6.862
Lecture: T9.30-11 (VIRTUAL) Recitation: R9.30-11 (VIRTUAL) or R11-12.30 (VIRTUAL) or R1-2.30 (VIRTUAL) or R2.30-4 (VIRTUAL) or F9.30-11 (VIRTUAL) or F11-12.30 (VIRTUAL) or F1-2.30 (VIRTUAL) or F2.30-4 (VIRTUAL) +final

Introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction; formulation of learning problems; representation, over-fitting, generalization; classification, regression, reinforcement learning; and methods such as linear classifiers, feed-forward, convolutional, and recurrent networks. Students taking graduate version complete different assignments. Meets with 6.036 when offered concurrently. Recommended prerequisites: 18.06 and 6.006. Enrollment limited; no listeners.
Fall: I. Drori
Spring: I. Drori
No required or recommended textbooks