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Searched for: 1 subject found.
6.3900 Introduction to Machine Learning
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Prereq: (6.1010 or 6.1210) and (18.03, 18.06, 18.700, or 18.C06)
Units: 4-0-8
URL: https://introml.mit.edu?from=registrar
Lecture: M3-4.30 (10-250) Lab: W9.30-11 (34-501) or W11-12.30 (34-501) or W11-12.30 (32-044) or W1-2.30 (34-501) or W1-2.30 (32-044) or W2.30-4 (34-501) Recitation: R11-12.30 (45-102) or R1-2.30 (32-044) or R2.30-4 (32-044) or F11-12.30 (45-102) +final
Introduction to the principles and algorithms of machine learning from an optimization perspective. Topics include linear and non-linear models for supervised, unsupervised, and reinforcement learning, with a focus on gradient-based methods and neural-network architectures. Previous experience with algorithms may be helpful.
Fall: S. Shen
Spring: S. Shen
No textbook information available
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