What does forward propagation mean in a neural network?

Correct answer: Performing successive computations on data from the input layer to the output layer

Forward propagation is the computation phase in which an input moves from the input layer through successive hidden layers to the output layer. Each layer performs weighted sums and usually applies an activation function, producing the next layer’s input and finally a prediction. Thus A is correct. Sending gradients backward is backpropagation, not forward propagation.