when an error is spotted, adjustments propagate back through the network to help correct it in the future. Keep doing this, modifying the weights again and again, and you gradually improve the performance of the neural network so that eventually it’s able to go all the way from taking in single pixels to learning the existence of lines, edges, shapes, and then ultimately entire objects in scenes. This, in a nutshell, is deep learning.
