國立虎尾科技大學 |

Learn Python Generative AI = journey from autoencoders to transformers to large language models /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Learn Python Generative AI / Zonunfeli Ralte, Indrajit Kar.
其他題名:	journey from autoencoders to transformers to large language models /
作者:	Ralte, Zonunfeli.
其他作者:	Kar, Indrajit,
面頁冊數:	1 online resource (349 pages)
標題:	COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition. -
電子資源:	https://portal.igpublish.com/iglibrary/search/BPB0000573.html
ISBN:	9789355517302

Learn Python Generative AI = journey from autoencoders to transformers to large language models /
Ralte, Zonunfeli.

Learn Python Generative AI journey from autoencoders to transformers to large language models /[electronic resource] ：Zonunfeli Ralte, Indrajit Kar. - 1 online resource (349 pages)

Includes bibliographical references and index.

Learn Python Generative AI : journey from autoencoders to transformers to large language models -- About the Authors -- About the Reviewers -- Acknowledgements -- Preface -- Errata -- Table of Contents -- Chapter 1 Introducing Generative AI -- Chapter 2 Designing Generative Adversarial Networks -- Chapter 3 Training and Developing Generative Adversarial Networks -- Chapter 4 Architecting Auto Encoder for Generative AI -- Chapter 5 Building and Training Generative Autoencoders -- Chapter 6 Designing Generative Variation Auto Encoder -- Chapter 7 Building Variational Autoencoders for Generative AI -- Chapter 8 Fundamental of Designing New Age Generative Vision Transformer -- Chapter 9 Implementing Generative Vision Transformer -- Chapter 10 Architectural Refactoring for Generative Modeling -- Chapter 11 Major Technical Roadblocks in Generative AI and Way Forward -- Chapter 12 Overview and Application of Generative AI Models -- Chapter 13 Key Learnings -- Index.

Access restricted to authorized users and institutions.

This book researches the intricate world of generative Artificial Intelligence, offering readers an extensive understanding of various components and applications in this field. The book begins with an in-depth analysis of generative models, providing a solid foundation and exploring their combination nuances. It then focuses on enhancing TransVAE, a variational autoencoder, and introduces the Swin Transformer in generative AI. The inclusion of cutting edge applications like building an image search using Pinecone and a vector database further enriches its content. The narrative shifts to practical applications, showcasing GenAI's impact in healthcare, retail, and finance, with real-world examples and innovative solutions. In the healthcare sector, it emphasizes AI's transformative role in diagnostics and patient care. In retail and finance, it illustrates how AI revolutionizes customer engagement and decision making. The book concludes by synthesizing key learnings, offering insights into the future of generative AI, and making it a comprehensive guide for diverse industries. Readers will find themselves equipped with a profound understanding of generative AI, its current applications, and its boundless potential for future innovations.

Mode of access: World Wide Web.

ISBN: 9789355517302Subjects--Topical Terms:

1483850
COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: Q335

Dewey Class. No.: 006.3

Learn Python Generative AI = journey from autoencoders to transformers to large language models /
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520 3 $a This book researches the intricate world of generative Artificial Intelligence, offering readers an extensive understanding of various components and applications in this field. The book begins with an in-depth analysis of generative models, providing a solid foundation and exploring their combination nuances. It then focuses on enhancing TransVAE, a variational autoencoder, and introduces the Swin Transformer in generative AI. The inclusion of cutting edge applications like building an image search using Pinecone and a vector database further enriches its content. The narrative shifts to practical applications, showcasing GenAI's impact in healthcare, retail, and finance, with real-world examples and innovative solutions. In the healthcare sector, it emphasizes AI's transformative role in diagnostics and patient care. In retail and finance, it illustrates how AI revolutionizes customer engagement and decision making. The book concludes by synthesizing key learnings, offering insights into the future of generative AI, and making it a comprehensive guide for diverse industries. Readers will find themselves equipped with a profound understanding of generative AI, its current applications, and its boundless potential for future innovations.
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