Backpropagation is an algorithm used for training artificial neural networks. It is a supervised learning technique that helps adjust the weights of the network to minimize the difference between the predicted outputs and the actual target outputs. The term "backpropagation" is short for "backward propagation of errors," signifying its two-step process: forward pass and backward pass.
