Neural Network Backpropagation Example With Activation Function

The simplest possible back propagation example done with the sigmoid activation function.
Some brief comments on how gradients are calculated in actual implementations.

Edit: there is a slight omission/error in the da/dw expression, as pointed out by Laurie Linnett. The video has da/dw = a(1-a), but it should be ia(1-a), because the argument to a is the function (iw), whose derivative (with respect to w) is i.

Видео Neural Network Backpropagation Example With Activation Function канала Mikael Laine