Just What Is Deep Learning, and What Does It Solve In Marketing?

How is a network trained? When given input data with a labeled answer (meaning it's already been classified), the deviation between the network's predictions and the actual answer produces an error signal. The error signal and non-linearity of each neuron's decision function tells us whether to increase or decrease each weight. The error signal gets propagated backwards all the way to the lowest layer. Over many training examples, the network weights are repeatedly tuned until finally reaching some satisfactory benchmark, such as accuracy level.