back propagation on a deep feet board neural network training and neural network has three major steps first it does a forward pass and makes a prediction second it compares the prediction to the ground truth using a loss function the loss function outputs an error value which is an estimate of how badly the network is performing last it uses the error value to do back propagation which calculates the gradients for each node in the network the gradient is a value used to adjust the network's internal weights allowing