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Backpropagation utilizes the chain rule of calculus to compute the gradient of the loss function with respect to each weight in the network. The chain rule allows the decomposition of the gradient into a series of simpler, local gradients that can be efficiently calculated layer by layer, from the output layer back to the input layer. Join our AI community for more posts like this @aibutsimple 🤖 #machinelearning #deeplearning #math #datascience
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