2,525 views since Nov 26, 2023

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An equally valuable form of support is to simply share some of the videos.
Special thanks to these supporters: http://3b1b.co/nn3-thanks
Written/interactive form of this series: https://www.3blue1brown.com/topics/ne...

This one is a bit more symbol-heavy, and that's actually the point. The goal here is to represent in somewhat more formal terms the intuition for how backpropagation works in part 3 of the series, hopefully providing some connection between that video and other texts/code that you come across later.

For more on backpropagation:
http://neuralnetworksanddeeplearning....
https://github.com/mnielsen/neural-ne...
http://colah.github.io/posts/2015-08-...

Music by Vincent Rubinetti:
https://vincerubinetti.bandcamp.com/a...

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Video timeline
0:00 - Introduction
0:38 - The Chain Rule in networks
3:56 - Computing relevant derivatives
4:45 - What do the derivatives mean?
5:39 - Sensitivity to weights/biases
6:42 - Layers with additional neurons
9:13 - Recap
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