Concept
Backpropagation
Backpropagation is the algorithm that computes gradients of a loss function with respect to every parameter in a neural network, by applying the chain rule from calculus backward through the network's layers.
The rest of “Backpropagation” is a premium feature: every concept in the library gets a precise, practitioner-focused write-up like this one, cross-linked straight from the paper summaries that use it.
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