MIT Subject Listing & Schedule
Fall 2018 Search Results

Searched for: "6.036"    Subjects offered any term

1 subject found.

6.036 Introduction to Machine Learning

(, )
Prereq: Calculus II (GIR) and (6.00 or 6.01)
Units: 4-0-8
Credit cannot also be received for 6.862
Lecture: T9.30-11 (32-123) Recitation: F9.30-11 (34-501) or F11-12.30 (34-501) or F1-2.30 (34-501) or F2.30-4 (34-501) or W11-12.30 (34-501) or W1-2.30 (34-501) +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; clustering, classification, probabilistic modeling; and methods such as support vector machines, hidden Markov models, and neural networks. Students taking graduate version complete additional assignments. Meets with 6.862 when offered concurrently. Recommended prerequisites: 6.006 and 18.06. Enrollment may be limited; no listeners.
L. Kaelbling
No textbook information available