What's actually happening to a neural network as it learns?
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The following video is sort of an appendix to this one. The main goal with the followon video is to show the connection between the visual walkthrough here, and the representation of these "nudges" in terms of partial derivatives that you will find when reading about backpropagation in other resources, like Michael Nielsen's book or Chis Olah's blog.

Video timeline:
0:00 Introduction
0:23 Recap
3:07 Intuitive walkthrough example
9:33 Stochastic gradient descent
12:28 Final words

Thanks to these viewers for their contributions to translations
Italian: @teobucci
Vietnamese: CyanGuy111