Generative adversarial networks cookbook : over 100 recipes to build generative models using Python, TensorFlow, and Keras /

Generative adversarial networks cookbook : over 100 recipes to build generative models using Python, TensorFlow, and Keras /

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Bibliographic Details
Author / Creator:	Kalin, Josh, author.
Imprint:	Birmingham : Packt, [2018] ©2018
Description:	1 online resource (261 pages)
Language:	English
Subject:	Machine learning. Neural networks (Computer science) Python (Computer program language) Neural Networks, Computer Machine Learning Machine learning Neural networks (Computer science) Python (Computer program language)
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/14139761

Hidden Bibliographic Details
ISBN:	1789139589 9781789139587
Notes:	Includes bibliographical references and index. Print version record.
Summary:	Generative Adversarial Networks have opened up many new possibilities in the machine learning domain. This book is all you need to implement different types of GANs using TensorFlow and Keras, in order to provide optimized and efficient deep learning solutions.
Other form:	Print version: Kalin, Josh. Generative Adversarial Networks Cookbook : Over 100 Recipes to Build Generative Models Using Python, TensorFlow, and Keras. Birmingham : Packt Publishing Ltd, ©2018 9781789139907

Description
Summary:	No detailed description available for "Generative Adversarial Networks Cookbook".
Physical Description:	1 online resource (261 pages)
Bibliography:	Includes bibliographical references and index.
ISBN:	1789139589 9781789139587