Neural networks are trained like any other algorithm. You want to get some results and provide information to the network to learn from. For example, we want our neural network to distinguish between photos of cats and dogs and provide plenty of examples.Delta is the difference between the data and the output of the neural network. We use calculus magic and repeatedly optimize the weights of the network until the delta is zero. Once the delta is zero or close to it, our model is correctly able to predict our example data.