Machine Learning, Deep Learning, Neural Networks, Data Science, Towards Data Science.
much as possible. So, in a GAN architecture, we have a discriminator, that takes samples of true and generated data and that try to classify them as well as possible, and a generator that is trained to fool the discriminator as much as possible. Let’s see on a simple example why the direct and