An intuitive explanation of the "Deep neural networks are universal function approximators" theorem

Part 1 (2018)
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Researcher Michael Nielsen recently wrote some research notes about a line of thinking, writing and teaching called “explorable explanation”. In the Magic Paper notes, he discussed and demonstrated a project called Magic Paper, and chose the universality theorem that @jeremy mentioned in Lesson 1 of Part1v2 as an example. I remember @zaoyang asking about the intuition behind this theorem in the Lesson 1 Wiki thread, so here’s the video:

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Thanks @poppingtonic, this is awesome :wink:

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Thanks for sharing.

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It’s really cool…
Thanks for the link…

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Great place to start and led to some other very cool web sites:

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thank you

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nice video, suprised I couldnt find this theorem discussed more in comparison to computability theorems