What is Backpropagation in Machine Learning?
Backpropagation is a fundamental algorithm used to compute the gradients of the model parameters in a
neural network. It is a key component of training
deep learning models using gradient-based optimization methods. Backpropagation efficiently computes the gradients by propagating the errors from the output layer to the input layer through the layers of the network.