The goal with ______ is to update each of the weights in the network so that they cause the actual output to be closer to the target output, thereby minimizing the error for each output neuron and the network as a whole.

A. forward propagation
B. backward propagation
C. iterative propagation

Correct Answer: B

Forward propagation is how neural networks make predictions. Input data is "forward propagated" through the network layer by layer to the final layer which outputs a prediction.

The goals of backward propagation are straightforward: adjust each weight in the network in proportion to how much it contributes to overall error. If we iteratively reduce each weight's error, eventually we'll have a series of weights the produce good predictions.