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No strong matches for “recursion”. Here are the closest videos.
MIT Godel Escher Bach Lecture 11:02:34

MIT Godel Escher Bach Lecture 1

557K views • 13 years ago
jasonofthel33t
The first lecture of an MIT course on Douglas Hofstadter's Godel, Escher, Bach, covering themes like self-reference, recursion and incompleteness. The full lecture series is on YouTube.
Lecture 1A: Overview and Introduction to Lisp1:12:56

Lecture 1A: Overview and Introduction to Lisp

420K views • 7 years ago
MIT OpenCourseWare
The first lecture of MIT's 6.001 (SICP) with Abelson and Sussman, giving an overview of the course and an introduction to Lisp. It argues that computer science is about managing complexity and abstraction, not computers.
The Josephus Problem - Numberphile13:58

The Josephus Problem - Numberphile

7M views • 10 years ago
Numberphile
Numberphile with Daniel Erman on the Josephus problem, where people in a circle are eliminated in turn. It shows how the survivor's position follows a neat pattern tied to powers of two and binary.
Lecture 1B | MIT 6.001 Structure and Interpretation, 198658:22

Lecture 1B | MIT 6.001 Structure and Interpretation, 1986

116K views • 17 years ago
MIT OpenCourseWare
Lecture 1B of MIT's 6.001 Structure and Interpretation of Computer Programs (1986) with Gerald Sussman, covering procedures, processes and the substitution model. It includes the line about the power of naming things.
Newsroom : Warcraft Sequel Lets You Play A Character Playing Warcraft2:59

Newsroom : Warcraft Sequel Lets You Play A Character Playing Warcraft

4.6M views • 18 years ago
The Onion
An Onion News Network satire about a Warcraft sequel in which you play a character who is playing Warcraft, in a cramped dark apartment.
WE MUST ADD STRUCTURE TO DEEP LEARNING BECAUSE...1:49:11

WE MUST ADD STRUCTURE TO DEEP LEARNING BECAUSE...

101K views • 2 years ago
Machine Learning Street Talk
Machine Learning Street Talk interviews Paul Lessard about Categorical Deep Learning, which uses category theory and monads to make neural network architectures more interpretable and composable. They also discuss neural networks' limits in reasoning and unbounded computation.