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A free and open online publication of educational material from thousands of MIT courses, covering the entire MIT curriculum, ranging from introductory to the most advanced graduate courses. On the OCW website, each course includes a syllabus, instructional material like notes and reading lists, and learning activities like assignments and solutions. Some courses also have videos, online textbooks, and faculty insights on teaching. Knowledge is your reward. There's no signup or enrollment, and no start or end dates. OCW is self-paced learning at its best. Whether you’re a student, a teacher, or simply a curious person that wants to learn, MIT OpenCourseWare (OCW) offers a wealth of insight, inspiration, videos, and a whole lot more! Get the full picture on the OCW website at https://ocw.mit.edu. Accessibility: https://accessibility.mit.edu/ User comments policy: https://ocw.mit.edu/comments/ (Channel banner photo by Nietnagel on Flickr: https://flic.kr/p/8WXxfK.)
Episodes


Lec 24. Inference Methods for Deep Learning

Lec 17. Generalization: Out-of-Distribution (OOD)

Lec 01. Introduction to Deep Learning

Lec 20. Scaling Laws

Lec 13. Representation Learning: Theory

Lec 10. Architectures: Memory

Lec 11. Representation Learning: Reconstruction-Based

Lec 14. Generative Models: Basics

Lec 03. Approximation Theory

Lec 12. Representation Learning: Similarity-Based

Lec 19. Transfer Learning: Data

Lec 23. Metrized Deep Learning

Lec 07. Scaling Rules for Optimization

Lec 21. Language Models

Lec 08. Architectures: Transformers

Lec 06. Generalization Theory

PyTorch Tutorial

Lec 18. Transfer Learning: Models

Lecture 08: Local Public Goods and Fiscal Federalism
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