Explore the power of Generative Adversarial Networks to empower your business About This Book * Use different datasets to build advanced projects in Generative Adversarial Networks domain *Implementing projects ranging from generating 3D shapes to Face aging application and so on. *Explore the power of GANs to empower your business offerings Who This Book Is For This book is intended for data scientists, machine learning developers, deep learning practitioners and AI enthusiasts who want a project guide to test their knowledge and expertise in building real-world GANs models. These full-fledged projects will help you master machine learning, and neural network principles. Basic understanding of machine learning and deep learning concepts will be handy. Hands-on experience in Tensorflow or Keras will be a plus point What You Will Learn * Training the network on the 3D Shapenet dataset to generate realistic shapes *Learn Keras implementation of DCGAN for anime character generation in Jupyter Notebook *Implementing a SRGAN network to generate high-resolution images *Training the Age-cGAN on IMDB Wiki Images dataset *Understanding of Conditional GAN for image-to-image translation *Generator and discriminator implementation of StackGAN in Keras In Detail Generative Adversarial Networks (GANs) potential is huge because they can learn to mimic any distribution of data. Major research and development work is going into the field since it is one of the growing areas of machine learning. This book will bring your skills to test while building 8 end-to-end projects in GANs domain. This book will start with the required concepts, tools/libraries that will be used to build efficient projects, thus giving you the foundation to get well versed with the concepts and principles. We will use different complexities of datasets in order to build end-to-end projects. With every chapter, the level of complexity and operations will become advanced thus providing you the grip over GAN domain. It consists of 8 projects covering popular approaches such as 3D-GAN, Age-cGAN, DCGAN, SRGAN, StackGAN, TextureGAN and CycleGAN. We will bring the real-world practical implementation of the models to understand the architecture and functioning of generative models. By the end of this book, you will be all ready to build, train, and optimize your own end-to-end GANs models at work or projects

Book Information
ISBN 9781789136678
Author Kailash Ahirwar
Format Paperback
Page Count 306
Imprint Packt Publishing Limited
Publisher Packt Publishing Limited