I'm currently working on constructing a neural network from scratch (in JavaScript). I'm in the middle of working on the backpropagation, but there's something I don't understand: how does the backprop algorithm know which weights to change or which paths to take? The way I did it, it always took all of the paths/weights and changed them all. So how does the algorithm know which paths to take, which weights to change, and whether to add or subtract X amount from said weight?

  • 3
    $\begingroup$ Basically using chain rule. Check this video and if it is your taste, the following one on the playlist with the mathematical details to get a better understanding of the process. This one might also help. $\endgroup$
    – serali
    Oct 6 '21 at 12:40

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