
MIT OpenCourseWare
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


Lecture 9.1: Tomaso Poggio - iTheory: Visual Cortex & Deep Networks

Lecture 7.1: Josh McDermott - Introduction to Audition, Part 1

Lecture 6.1: Nancy Kanwisher - Introduction to Social Intelligence

Unit 3 Debate: Tomer Ullman and Laura Schulz

Unit 8 Panel: Robotics

Lecture 1.3: James DiCarlo - Neural Mechanisms of Recognition Part 1

Seminar 5: Tom Mitchell - Neural Representations of Language

Lecture 1.5: Winrich Freiwald - Primates, Faces, & Intelligence

Lecture 5.3: Patrick Winston - Story Understanding

Lecture 3.1: Liz Spelke - Cognition in Infancy (Part 1)

Lecture 4.3. Aude Oliva - Predicting Visual Memory

Lecture 1.1: Nancy Kanwisher - Human Cognitive Neuroscience

Lecture 5.1: Vision and Language

Lecture 8.4: Stefanie Tellex - Human-Robot Collaboration

Lecture 2.2: Josh Tenenbaum - Computational Cognitive Science Part 2

Lecture 2.3: Josh Tenenbaum - Computational Cognitive Science Part 3

Tutorial 5.2: Tomer Ullman - Church Programming Language Part 2

Alon Baram & Laurie Bayet: Learning to Recognize Digits and Faces from Few Examples

Tutorial 4: Ethan Meyers - Understanding Neural Content via Population Decoding
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