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  • Generative Adversarial Networks (GANs)

    Generative Adversarial Networks (GANs) by Kuzmiakova, Adele;

      • GET 10% OFF

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      • Publisher's listprice GBP 149.00
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        71 184 Ft (67 795 Ft + 5% VAT)
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    71 184 Ft

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    Product details:

    • Publisher Arcler Press
    • Date of Publication 31 December 2025

    • ISBN 9781779564177
    • Binding Hardback
    • No. of pages240 pages
    • Size 229x152 mm
    • Weight 666 g
    • Language English
    • 700

    Categories

    Short description:

    Discover how GANs revolutionize AI by pitting neural networks against each other to create lifelike images, text, and data. Dive into their architecture, training methods, and multifaceted applications across healthcare, media, and research, offering key insights for students, data scientists, and AI practitioners.

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    Long description:

    Generative Adversarial Networks (GANs) are a class of machine learning models that have transformed the fields of artificial intelligence and creative technologies. By pitting two neural networks against each other, GANs generate highly realistic data, from images to text. This book explores the architecture, training methods, and diverse applications of GANs in healthcare, media, and research. With its in-depth analysis, it is essential for students, data scientists, and AI practitioners seeking to master this groundbreaking technology.

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    Table of Contents:

    • Chapter 1 Introduction to Generative Adversarial Networks (GANs)
    • Chapter 2 Architecture of Generative Adversarial Networks
    • Chapter 3 Types of Generative Adversarial Networks
    • Chapter 4 Training Generative Adversarial Networks (GANs)
    • Chapter 5 Security Issues in Generative Adversarial Networks
    • Chapter 6 Image Editing Using GANs
    • Chapter 7 Practical Applications of GANs
    • Chapter 8 Advanced Concepts in GANs

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