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AI & Machine Learning · Intermediate

Backpropagation

The algorithm that computes gradients of the loss with respect to every weight by applying the chain rule backward through the network.

Definition

After a forward pass computes predictions and loss, backpropagation propagates error signals from the output layer back to earlier layers, giving each parameter's gradient. An optimizer then uses these gradients to update weights.

Exam tip

Backpropagation computes gradients; gradient descent (the optimizer) applies them.

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