Talk202429 h 32 min640×360Subtitles

MIT 6.7960 Deep Learning, Fall 2024

MIT OpenCourseWare

EducationScience

Clips are not offered for this film yet: it is in several files, and clips are cut from a film in one.

Low resolution (640×360): this is the archive's own copy.

Parts

About

Instructors: Phillip Isola, Sara Beery, Dr. Jeremy Bernstein

View the complete course: https://ocw.mit.edu/courses/6-7960-deep-learning-fall-2024/

YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63URZnh5iqBzDTDYPUTQT-8

This course covers the fundamentals of deep learning, including both theory and applications. Topics include neural net architectures (MLPs, CNNs, RNNs, graph nets, transformers), geometry and invariances in deep learning, backpropagation and automatic differentiation, learning theory and generalization in high dimensions, and applications to computer vision, natural language processing, and robotics.

License: Creative Commons BY-NC-SA

More information at https://ocw.mit.edu/terms

More courses at https://ocw.mit.edu

Support OCW at http://ow.ly/a1If50zVRlQ

We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.

Archive
Internet Archive, in MIT OpenCourseWare
Licence or status
CC BY-NC-SA 4.0, as the Internet Archive states it.
Credit
MIT OpenCourseWare
Language
English
Subtitles
English
Who can watch
The archive gives no rating. Invisible Network shows it to Tweens profiles and older, judged from its collection and subjects. How films are placed