Book

Generative adversarial networks projects : build next-generation generative models using TensorFlow and Keras

Ahirwar, Kailash, author

Overview

Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you'll gain an understanding of the architecture and functioning of generative models through their practical implementation.

• Publisher: Packt
• Subject: Machine learning. / Neural networks (Computer science) / Artificial intelligence.
• ISBN: 9781789136678, 1789136679

Item info:

1 item available

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Holdings :

Call Number	Copies	Material	Location
QA76.87.A45 2019	1	BOOK	GENERAL