The GAN framework has revolutionized the fields of machine learning and deep learning. Over the course of the chapters in this book, we implemented many models in many domains that were part of this revolution, including images, text, and audio.
What we've GANed so far
Generative models
We learned about deep learning and generative models in general, and their applications in AI. We covered many topics including GANs, autoregressive models, variational autoencoders, and reversible flow models.
We described in detail the building blocks of GANs, including their strengths and limitations. We learned how to visualize their results and how to evaluate them qualitatively and quantitatively.
