A Beginner's Guide to Generative AI: An Introductory Path to Diffusion Models, Chatgpt, and Llms
暫譯: 生成式人工智慧入門指南：擴散模型、ChatGPT 與大型語言模型的入門之路

Bhati, Deepshikha, Neha, Fnu, Guercio, Angela

A Beginner's Guide to Generative AI: An Introductory Path to Diffusion Models, Chatgpt, and Llms
  • 出版商: Springer
  • 出版日期: 2025-07-22
  • 售價: $1,830
  • 貴賓價: 9.5 折 $1,739
  • 語言: 英文
  • 頁數: 236
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031847237
  • ISBN-13: 9783031847233
  • 相關分類: 人工智慧

    • 海外代購書籍(需單獨結帳)

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商品描述

This book is the essential guide for anyone curious about AI's creative power. In the rapidly evolving landscape of artificial intelligence, generative AI stands out as one of the most transformative technologies of our time. Designed for beginners and requiring no prior knowledge of AI, this book breaks down the fundamentals of generative AI, from text and image generation to the workings of models like ChatGPT and Google Bard. The authors provide step-by-step coverage of the essential concepts and techniques that power generative AI. From the basics of how machines learn to generate text and images, to the intricate workings of models like Transformers, ChatGPT, and Google Bard, readers will gain a solid foundation in AI's most cutting-edge tools. Rather than focusing on a single method, the authors introduce a spectrum of generative modeling techniques, including diffusion models, variational autoencoders, and transformers. This comprehensive exposure ensures readers will be well-prepared to understand and adapt to the rapidly evolving AI landscape. In addition, real-world applications of generative AI across various industries are explored including healthcare innovations, business analytics, and legal technology, and the authors provide practical insights and examples that show how generative AI is revolutionizing these fields.

商品描述(中文翻譯)

這本書是對於任何對人工智慧創造力感到好奇的人的必備指南。在快速演變的人工智慧領域中，生成式人工智慧（generative AI）脫穎而出，成為我們這個時代最具變革性的技術之一。本書專為初學者設計，無需具備人工智慧的先前知識，從文本和圖像生成到像 ChatGPT 和 Google Bard 這樣的模型運作，逐步解析生成式人工智慧的基本概念。作者提供了關於驅動生成式人工智慧的基本概念和技術的逐步介紹。從機器如何學習生成文本和圖像的基礎知識，到像 Transformers、ChatGPT 和 Google Bard 這樣的模型的複雜運作，讀者將獲得人工智慧最前沿工具的堅實基礎。作者不僅專注於單一方法，而是介紹了一系列生成建模技術，包括擴散模型（diffusion models）、變分自編碼器（variational autoencoders）和變壓器（transformers）。這種全面的接觸確保讀者能夠充分準備理解和適應快速演變的人工智慧環境。此外，書中還探討了生成式人工智慧在各行各業的實際應用，包括醫療創新、商業分析和法律科技，並提供了實用的見解和範例，展示生成式人工智慧如何徹底改變這些領域。

作者簡介

Deepshikha Bhati is a Lecturer in the Department of Computer Science at Kent State University. Prior to her current role, she built a strong foundation in both industry and academia, holding various teaching and research positions. Her academic journey includes deep expertise in generative AI LLM models, explainable AI (XAI), information visualization, image processing, deep learning (DL), and machine learning (ML). Ms. Bhati is a member of IEEE, the IEEE Computer Society, and ACM.

Fnu Neha is a Ph.D. candidate in the Department of Computer Science at Kent State University, with over six years of experience in research and teaching, particularly in artificial intelligence (AI), deep learning, and databases. Her Ph.D. research focuses on developing deep learning techniques and AI-based software to analyze renal CT scans and correlate them with radiography and biopsy-based features for the accurate classification of small renal masses and subtypes of renal cell carcinoma (RCC).

Angela Guercio, Ph.D., is an Associate Professor of Computer Science at Kent State University, where she has worked for 19 years. Prior to joining Kent State University, she served as an Assistant Professor at Hiram College for three years and as a Senior Research Associate at the University of Salerno, Italy, for 16 years. Her research interests include smart e-education and AI, big data, data mining, software engineering, visual languages, human-machine interaction, and multimedia computing. She has co-authored numerous papers published in scientific journals and refereed international conferences. Dr. Guercio has received multiple research awards and fellowships for her work. Dr. Guercio is a member of IEEE, the IEEE Computer Society, and ACM.

Md Amiruzzaman, Ph.D., is an Assistant Professor in the Department of Computer Science at West Chester University. Before joining West Chester University, he worked as a software developer for almost 10 years for several companies. He has also held the position of Assistant Professor at Kent State University. In the past, he has worked as a Research Assistant at Sejong University and Korea University. His research interests include visual analytics of urban data, data mining, machine learning, deep learning, and data hiding.

Aloysius Bathi Kasturiarachi, Ph.D. has been at Kent State University since 1995 as a faculty member in the Department of Mathematical Sciences. He teaches courses in mathematics and computer science. He won the Distinguished Teaching Award in 2001 and was a finalist in 2022. He is the recipient of numerous grants. He also served as the Associate Dean for Academic Affairs at Kent State University at Stark from August 2013 to January 2018. His research interests include partial differential equations, non-integrable systems, numerical analysis, mathematics education, and number theory. He has published extensively in these areas. He is a member of MAA and AMS.

作者簡介(中文翻譯)

Deepshikha Bhati 是肯特州立大學計算機科學系的講師。在擔任目前職位之前，她在產業和學術界建立了堅實的基礎，擔任過多個教學和研究職位。她的學術旅程包括在生成式 AI LLM 模型、可解釋 AI (XAI)、資訊視覺化、影像處理、深度學習 (DL) 和機器學習 (ML) 方面的深厚專業知識。Bhati 女士是 IEEE、IEEE 計算機學會和 ACM 的成員。

Fnu Neha 是肯特州立大學計算機科學系的博士候選人，擁有超過六年的研究和教學經驗，特別是在人工智慧 (AI)、深度學習和資料庫方面。她的博士研究專注於開發深度學習技術和基於 AI 的軟體，以分析腎臟 CT 掃描，並將其與放射學和活檢特徵相關聯，以準確分類小型腎腫塊和腎細胞癌 (RCC) 的亞型。

Angela Guercio 博士是肯特州立大學的計算機科學副教授，已在該校工作 19 年。在加入肯特州立大學之前，她曾在海勒姆學院擔任助理教授三年，並在意大利薩勒諾大學擔任高級研究助理 16 年。她的研究興趣包括智慧電子教育和 AI、大數據、資料挖掘、軟體工程、視覺語言、人機互動和多媒體計算。她共同撰寫了多篇發表於科學期刊和國際會議的論文。Guercio 博士因其研究工作獲得多項研究獎和獎學金。Guercio 博士是 IEEE、IEEE 計算機學會和 ACM 的成員。

Md Amiruzzaman 博士是西切斯特大學計算機科學系的助理教授。在加入西切斯特大學之前，他在多家公司擔任了近 10 年的軟體開發人員。他還曾在肯特州立大學擔任助理教授。過去，他曾在世宗大學和韓國大學擔任研究助理。他的研究興趣包括城市數據的視覺分析、資料挖掘、機器學習、深度學習和數據隱藏。

Aloysius Bathi Kasturiarachi 博士自 1995 年以來一直在肯特州立大學數學科學系任教。他教授數學和計算機科學的課程。他於 2001 年獲得傑出教學獎，並在 2022 年成為決賽入圍者。他獲得了多項資助。他還曾於 2013 年 8 月至 2018 年 1 月擔任肯特州立大學斯塔克校區的學術事務副院長。他的研究興趣包括偏微分方程、不可積系統、數值分析、數學教育和數論。他在這些領域發表了大量著作。他是 MAA 和 AMS 的成員。

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