Generative Adversarial Networks in Practice / (Record no. 45909)

MARC details
000 -LEADER
fixed length control field 03842cam a2200361M 4500
003 - CONTROL NUMBER IDENTIFIER
control field FlBoTFG
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251013120123.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 231119s2023 flu o ||| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1003805493
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781003805496
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781003281344
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1003281346
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781003805533
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781032248448
041 ## - LANGUAGE CODE
Language English
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 000000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 012040
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UY
Source bicssc
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.32
Edition number 23/eng/20231213
Item number GHA
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Ghayoumi, Mehdi.
245 10 - TITLE STATEMENT
Title Generative Adversarial Networks in Practice /
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc BOCA RATON :
Name of publisher, distributor, etc CHAPMAN & HALL CRC,
Date of publication, distribution, etc 2023.
300 ## - PHYSICAL DESCRIPTION
Extent 670 Pages :
Other physical details 216 B/W Illustrations ;
505 ## - FORMATTED CONTENTS NOTE
Contents 1. Introduction<br/><br/>2. Data Preprocessing<br/><br/>3. Model Evaluation<br/><br/>4. TensorFlow and Keras Fundamentals<br/><br/>5. Artificial Neural Networks Fundamentals and Architectures<br/><br/>6. Deep Neural Networks (DNNs) Fundamentals and Architectures<br/><br/>7. Generative Adversarial Networks (GANs) Fundamentals and Architectures<br/><br/>8. Deep Convolutional Generative Adversarial Networks (DCGANs)<br/><br/>9. Conditional Generative Adversarial Network (cGAN)<br/><br/>10. Cycle Generative Adversarial Network (CycleGAN)<br/><br/>11. Semi-Supervised Generative Adversarial Network (SGAN)<br/><br/>12. Least Squares Generative Adversarial Network (LSGAN)<br/><br/>13. Wasserstein Generative Adversarial Network (WGAN)<br/><br/>14. Generative Adversarial Networks (GANs) for Images<br/><br/>15. Generative Adversarial Networks (GANs) for Voice, Music, and Song<br/><br/>Appendix
520 ## - SUMMARY, ETC.
Summary, etc This book is an all-inclusive resource that provides a solid foundation on Generative Adversarial Networks (GAN) methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts. Key Features: Guides you through the complex world of GANs, demystifying their intricacies Accompanies your learning journey with real-world examples and practical applications Navigates the theory behind GANs, presenting it in an accessible and comprehensive way Simplifies the implementation of GANs using popular deep learning platforms Introduces various GAN architectures, giving readers a broad view of their applications Nurture your knowledge of AI with our comprehensive yet accessible content Practice your skills with numerous case studies and coding examples Reviews advanced GANs, such as DCGAN, cGAN, and CycleGAN, with clear explanations and practical examples Adapts to both beginners and experienced practitioners, with content organized to cater to varying levels of familiarity with GANs Connects the dots between GAN theory and practice, providing a well-rounded understanding of the subject Takes you through GAN applications across different data types, highlighting their versatility Inspires the reader to explore beyond this book, fostering an environment conducive to independent learning and research Closes the gap between complex GAN methodologies and their practical implementation, allowing readers to directly apply their knowledge Empowers you with the skills and knowledge needed to confidently use GANs in your projects Prepare to deep dive into the captivating realm of GANs and experience the power of AI like never before with Generative Adversarial Networks (GANs) in Practice. This book brings together the theory and practical aspects of GANs in a cohesive and accessible manner, making it an essential resource for both beginners and experienced practitioners.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Neural networks (Computer science)
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://ezproxy.lib.gla.ac.uk/login?url=https://www.taylorfrancis.com/books/9781003281344">https://ezproxy.lib.gla.ac.uk/login?url=https://www.taylorfrancis.com/books/9781003281344</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type General Books
506 ## - RESTRICTIONS ON ACCESS NOTE
Terms governing access Access restricted to subscribing institutions.
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Taylor & Francis
Public note Connect to resource
907 ## - LOCAL DATA ELEMENT G, LDG (RLIN)
a .b41198955
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Location Shelving location Date of Cataloging Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Non-fiction CUTN Central Library CUTN Central Library Generalia 13/10/2025   006.32 GHA 54564 13/10/2025 13/10/2025 General Books