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In machine learning, backpropagation is a gradient computation method commonly used for training a neural network in computing parameter updates.

It is an efficient application of the chain rule to neural networks. Backpropagation efficiently computes the gradient of the loss with respect to the network weights for a single input-output example. It does this

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