Intro to Adversarial Machine Learning and Generative Adversarial Networks - KDnuggets

Machine learning is an ever-evolving field, so it can be easy to feel like you're out of the loop on the latest developments changing the world this week. One of those emerging areas that have been getting a lot of buzz lately is GANs--or generative adversarial networks. So to keep you in the machine learning loop, we've put together a short crash course on GANs: With generative models, the aim is to model the distribution of a given dataset. For the generative models that we're talking about today, that dataset is usually a set of images, but it could also be other kinds of data, like audio samples or time-series data. There are two ways to go about getting a model of this distribution: implicitly or explicitly.