Backpropagation

Backpropagation is a method used in artificial neural networks to improve their accuracy by adjusting the weights of the connections based on the error rate obtained in the previous run (i.e., the difference between the actual output and the predicted output). It is a fundamental part of training deep learning models, allowing them to learn from their mistakes and make better predictions over time.