Generative AI in R: Transforming Data Science with Synthetic Data and Advanced Modeling Techniques
暫譯: R中的生成式AI：利用合成數據和先進建模技術轉變數據科學

Singh, Akansha, Singh, Krishna Kant

Generative AI in R: Transforming Data Science with Synthetic Data and Advanced Modeling Techniques
  • 出版商: Apress
  • 出版日期: 2025-12-18
  • 售價: $1,710
  • 貴賓價: 9.5 折 $1,625
  • 語言: 英文
  • 頁數: 580
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798868817625
  • ISBN-13: 9798868817625
  • 相關分類: R 語言、GAN 生成對抗網絡

    • 海外代購書籍(需單獨結帳)

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商品描述

Leverage Generative AI within the R programming environment and prepare for future directions and how new innovations can be applied in the R ecosystem. This pioneering book is designed to bridge the gap between the advanced realms of Generative AI and the practical, statistical computing power of R.

You'll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. You'll then dive into the practicalities of implementing generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) in R. See how R, most known for its statistical analysis, can also be used for creative synthetic data, improving model robustness, and generating innovative insights from data.

Additionally, this book addresses the demand for ethical AI by emphasizing the use of synthetic data to tackle privacy and data scarcity issues--concerns particularly relevant in healthcare, finance, and social research. We are at a pivotal moment in the evolution of AI and data science. With AI's growing importance, the book's focus on R makes advanced techniques more accessible, promoting ethical and innovative data science practice, preparing readers for upcoming trends.

商品描述(中文翻譯)

利用生成式人工智慧（Generative AI）於 R 程式環境中，並為未來的發展方向做好準備，了解新創新如何應用於 R 生態系統。本書旨在彌合生成式人工智慧的高級領域與 R 的實用統計計算能力之間的鴻溝。

您將首先了解生成式人工智慧的原則及其在當前數據驅動環境中的重要性。接著，您將深入探討在 R 中實現生成模型的實務，例如生成對抗網絡（Generative Adversarial Networks, GANs）和變分自編碼器（Variational Autoencoders, VAEs）。了解 R 如何不僅以其統計分析而聞名，還能用於創造性合成數據、提高模型的穩健性，並從數據中生成創新的見解。

此外，本書還針對倫理人工智慧的需求，強調使用合成數據來解決隱私和數據稀缺問題——這些問題在醫療、金融和社會研究中特別相關。我們正處於人工智慧和數據科學演變的關鍵時刻。隨著人工智慧日益重要，本書對 R 的重點使高級技術變得更易於接觸，促進倫理和創新的數據科學實踐，為讀者準備即將到來的趨勢。

作者簡介

Akansha Singh is a professor in the School of Computer Science and Engineering at Bennett University, Greater Noida, India. With an impressive academic background that includes a B.Tech, M. Tech, and a Ph.D. in Computer Science from IIT Roorkee, her expertise lies primarily in image processing, deep learning and machine learning. Dr. Singh's academic contributions extend beyond teaching; she has played significant roles as an Associate Editor and Guest Editor for several scholarly journals.

She has written more than 100 research papers in reputed journals, conferences, and books and authored more than 30 books in advanced computer science areas. Her dedication to research is evident through her leadership in government-funded projects as a Principal Investigator. Her research interests encompass a broad range of topics, including image processing, remote sensing, IoT, and machine learning.

Krishna Kant Singh serves as the Director of the Delhi Technical Campus, Greater Noida, India, bringing a wealth of teaching and research experience to his role. He hold multiple degrees, including a B. Tech, M. Tech, MS, and a Ph.D. from IIT Roorkee, all focused on image processing and Machine Learning. Dr. Singh has authored over 140 research papers in esteemed Scopus and SCIE indexed journals, along with 25 technical books, showcasing his profound impact on the field.

He is also the associate editor of IEEE ACCESS and many other journals of high repute. He has also served as a Guest Editor for Open Computer Science, Wireless Personal Communications, Complex and Intelligent systems, and many other journals. Additionally, his involvement in the Editorial Board of Applied Computing and Geosciences (Elsevier) highlights his significant contributions to academia and research.

作者簡介(中文翻譯)

阿坎莎·辛格是印度大諾伊達班尼特大學計算機科學與工程學院的教授。她擁有令人印象深刻的學術背景，包括來自印度理工學院魯爾基分校的B.Tech、M.Tech和計算機科學博士學位，專長主要在於影像處理、深度學習和機器學習。辛格博士的學術貢獻不僅限於教學，她還在多本學術期刊中擔任副編輯和客座編輯，發揮了重要的作用。

她在知名期刊、會議和書籍上發表了超過100篇研究論文，並在高級計算機科學領域撰寫了超過30本書籍。她對研究的奉獻精神通過作為主要研究者領導政府資助的項目得以體現。她的研究興趣涵蓋廣泛的主題，包括影像處理、遙感、物聯網和機器學習。

克里希納·坎特·辛格擔任印度大諾伊達德里技術校區的主任，為他的角色帶來了豐富的教學和研究經驗。他擁有多個學位，包括B.Tech、M.Tech、MS和來自印度理工學院魯爾基分校的博士學位，所有學位均專注於影像處理和機器學習。辛格博士在受尊敬的Scopus和SCIE索引期刊上發表了超過140篇研究論文，並撰寫了25本技術書籍，展示了他對該領域的深遠影響。

他還是IEEE ACCESS及其他多本高聲譽期刊的副編輯。他曾擔任《開放計算機科學》、《無線個人通信》、《複雜與智能系統》等多本期刊的客座編輯。此外，他在《應用計算與地球科學》（Elsevier）的編輯委員會中的參與，突顯了他對學術和研究的重要貢獻。

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