Concept
Backward propagation, or backpropagation, is a fundamental algorithm used in training artificial neural networks, allowing the network to update its weights by calculating the gradient of the loss function with respect to each weight through the chain rule. This process iteratively minimizes the error by propagating the loss backward from the output layer to the input, thus optimizing the network's performance on a given task.
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