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How do you backpropagate with a Convolutional Neural Network?
How does the calculation of gradients work?
In a Convolutional Neural Network, each layer is composed of filters. During backpropagation, the gradients of the loss function are propagated backwards through the layers. The gradients of the loss function with respect to the weights in each filter are then calculated using the chain rule.