CNN Backpropagation Part 2 | How Backpropagation works on Convolution, Maxpooling and Flatten Layers

This video explains in great detail how the backpropagation algorithm works in the case of CNN. We will learn how to apply backprop on flatten, maxpooling and convolution layers.

I recommend you watch the 1st part before watching this one. Here is the link:
Backpropagation in CNN | Part 1 | Dee...

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⌚Time Stamps⌚

00:00 - intro
00:05 - Backpropagation in CNN explained for convolution, max pooling, and flatten layers
01:23 - Recap/Back Propogation in CNN
02:46 - Backpropagation involves applying gradients to update weights and calculate loss
07:46 - Changing w1 affects Z1.
11:53 - Backpropagation in Maxpooling Layers
17:31 - Backpropagation on max pooling works by selecting the maximum item in each window
21:23 - The Backpropagation process involves minimizing the inverse of max pooling and calculating the derivative of Z1.
25:07 - Backpropagation process for Convolution, Maxpooling, and Flatten layers
30:48 - Backpropagation involves expanding and differentiating expressions to calculate derivatives.
36:35 - Backpropagation involves multiplication and deconvolution operations.