Generative Adversarial Networks Projects : Build Next-Generation Generative Models Using TensorFlow and Keras.

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Bibliographic Details
Author / Creator:	Ahirwar, Kailash.
Imprint:	Birmingham : Packt Publishing Ltd, 2019.
Description:	1 online resource (310 pages)
Language:	English
Subject:	Machine learning. Neural networks (Computer science) Artificial intelligence. Artificial intelligence. Machine learning. Neural networks (Computer science)
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/12542028

Hidden Bibliographic Details
ISBN:	9781789134193 1789134196
Notes:	Training the DCGAN Print version record.
Summary:	In this book, 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. It consists of 8 full-fledged projects covering approaches such as 3D-GAN, Age-cGAN, DCGAN, SRGAN, StackGAN, and CycleGAN with real-world use cases.
Other form:	Print version: Ahirwar, Kailash. Generative Adversarial Networks Projects : Build Next-Generation Generative Models Using TensorFlow and Keras. Birmingham : Packt Publishing Ltd, ©2019 9781789136678

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