we don't want to learn like very specific pinpoints of the training data that don't generalize well to test data now as we've seen before this is actually crucial for our models to be able to generalize to our test data so this is very important the most popular regularization technique deep learning is this very basic idea of drop out now the idea of drop out is well actually let's start with by revisiting this picture of a neural network that we had introduced previously and drop out during training we randomly set some of these activations of the hidden neurons to