Backpropagation

Also called: backprop, back propagation, backward pass

The calculation that works out how much each weight in a neural network contributed to an error, layer by layer from the output back, so gradient descent knows how to adjust it.

For example: After the model guesses wrong, backpropagation assigns a share of the blame to each of its millions of weights.