MIT Subject Listing & Schedule
Fall 2025 Search Results

Searched for:

1 subject found.

6.7900 Machine Learning

()
Prereq: 18.06 and (6.3700, 6.3800, or 18.600)
Units: 3-0-9
Lecture: TR2.30-4 (32-123) Recitation: F10 (45-102) or F11 (45-102) or F1 (45-102) or F2 (45-102) or F12 (45-102) or F3 (45-102) +final

Principles, techniques, and algorithms in machine learning from the point of view of statistical inference; representation, generalization, and model selection; and methods such as linear/additive models, active learning, boosting, support vector machines, non-parametric Bayesian methods, hidden Markov models, Bayesian networks, and convolutional and recurrent neural networks. Recommended prerequisite: 6.3900 or other previous experience in machine learning. Enrollment may be limited.
T. Broderick
No textbook information available