Generative adversarial networks and deep learning : theory and applications This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This books major goal is to concentrate on cutting edge research in deep learning and generative adversarial networks which includes creating new tools and methods for processing text images and audio. A generative adversarial network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology including computer vision security multimedia and advertisements image generation image translation text to images synthesis video synthesis generating high resolution images drug discovery etc