Advanced Deep Learning with Python

Intuition and justification of generative models

So far, we've used neural networks as discriminative models. This simply means that, given input data, a discriminative model will map it to a certain label (in other words, a classification). A typical example is the classification of MNIST images in 1 of 10 digit classes, where the neural network maps input data features (pixel intensities) to the digit label. We can also say this in another way: a discriminative model gives us the probability of (class), given (input). In the case of MNIST, ...