Generative Adversarial Networks (GANs)

Author:   Russ Elektran
Publisher:   Independently Published
ISBN:  

9798322644088


Pages:   296
Publication Date:   12 April 2024
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Generative Adversarial Networks (GANs)


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Overview

"Unlock the power of Generative Adversarial Networks (GANs) with this comprehensive guidebook, designed to take you from a basic understanding to mastering the art and science behind these transformative neural networks. Whether you're a student, researcher, or professional in computer science and artificial intelligence, this book offers an accessible yet thorough exploration of GANs, covering foundational concepts, mathematical principles, diverse architectures, and ground-breaking applications. ""Generative Adversarial Networks (GANs)"" demystifies complex ideas through a structured presentation, starting with an introduction to GANs, diving into their mathematical underpinnings, and unfolding their architectural intricacies. Learn the best practices for training GANs, navigating common challenges, and evaluating performance to ensure high-quality outcomes. The book not only explains the various types of GANs and their specific uses but also showcases their incredible potential across different sectors-from creating realistic images to advancing drug discovery and beyond. With a step-by-step guide to building your own GAN model, this book empowers you to put theory into practice. It addresses common pitfalls, offers solutions to typical challenges, and provides insights into advanced topics for those looking to push the limits of what GANs can achieve. Whether you're aiming to understand the basic mechanisms of GANs or explore the frontiers of artificial intelligence research, this book is your go-to resource for all things GANs. Embark on this learning journey to leverage the full capabilities of Generative Adversarial Networks and unlock new possibilities in AI and machine learning."

Full Product Details

Author:   Russ Elektran
Publisher:   Independently Published
Imprint:   Independently Published
Dimensions:   Width: 15.20cm , Height: 1.60cm , Length: 22.90cm
Weight:   0.399kg
ISBN:  

9798322644088


Pages:   296
Publication Date:   12 April 2024
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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