Natural Language Processing and Large Language Models: Theory, Hand-On Codes, and Case Studies
暫譯: 自然語言處理與大型語言模型：理論、實作代碼與案例研究
Zong, Chengqing, Zhao, Yang, Ma, Yanjun
- 出版商: Springer
- 出版日期: 2026-07-25
- 售價: $2,840
- 貴賓價: 9.5 折 $2,698
- 語言: 英文
- 頁數: 394
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 9819206812
- ISBN-13: 9789819206810
-
相關分類:
Natural Language Processing、Large language model
海外代購書籍(需單獨結帳)
相關主題
商品描述
This open access book unlocks the full potential of Natural Language Processing (NLP) through a comprehensive and hands-on guide that bridges foundational theory and cutting-edge practice. Whether you're a student, researcher, or industry practitioner, it enables you to build and deploy state-of-the-art NLP models--from classical statistical approaches to modern neural architectures and large language models (LLMs)--with confidence and clarity.
Unlike traditional texts that focus solely on concepts, this book offers a practical journey through real-world NLP applications, including sentiment analysis, information extraction, summarization, text matching, question answering, and machine translation. Each chapter is grounded in executable code and datasets, presented in the form of Jupyter Notebooks hosted on Baidu AI Studio. Readers can access free cloud-based resources to run, test, and modify models, making the learning experience interactive and scalable.
Designed for senior undergraduate and graduate students in computer science and AI-related fields, as well as NLP beginners and developers, the book demystifies key concepts such as Transformer, BERT, GPT, ERNIE, and RLHF through step-by-step case studies. It also addresses practical challenges--such as data preprocessing, model fine-tuning, and deployment--that reflect real-world R&D scenarios. Readers don't just learn what works in NLP--they understand how and why it works.
With its task-driven structure, fully tested codebase, and ready-to-use implementations, this book serves as a valuable academic and technical resource for anyone seeking to master applied NLP with modern deep learning techniques.
商品描述(中文翻譯)
這本開放存取的書籍充分發揮了自然語言處理（Natural Language Processing, NLP）的潛力，提供了一個全面且實用的指南，橋接了基礎理論與前沿實踐。無論您是學生、研究者還是業界從業者，它都能讓您自信且清晰地構建和部署最先進的NLP模型——從傳統的統計方法到現代的神經架構和大型語言模型（Large Language Models, LLMs）。
與僅專注於概念的傳統文本不同，這本書提供了一個實用的旅程，涵蓋了現實世界中的NLP應用，包括情感分析、信息提取、摘要生成、文本匹配、問答系統和機器翻譯。每一章都基於可執行的代碼和數據集，以Jupyter Notebooks的形式呈現，並托管在百度AI Studio上。讀者可以訪問免費的雲端資源來運行、測試和修改模型，使學習體驗互動且可擴展。
本書專為計算機科學和人工智慧相關領域的高年級本科生和研究生，以及NLP初學者和開發者設計，通過逐步的案例研究，揭示了Transformer、BERT、GPT、ERNIE和RLHF等關鍵概念的奧秘。它還解決了反映現實世界研發場景的實際挑戰——如數據預處理、模型微調和部署。讀者不僅學習NLP中有效的方法，還理解其運作的方式和原因。
憑藉其以任務為驅動的結構、經過全面測試的代碼庫和現成的實現，本書成為任何希望掌握應用NLP與現代深度學習技術的學術和技術資源。
作者簡介
Chengqing Zong received the Ph.D. degree in computer science from Institute of Computing Techonology, Chinese Academy of Sciences, China in March 1998. He is currently a professor with Institute of Automation, Chinese Academy of Sciences, China. His research interests include natural language processing, machine translation, and cognitive language computing. He has published more than 200 papers in top-tier conferences and journals. He has authored and co-authored six books, including Text Data Mining, which was published with Springer in 2021. He is a member of the Academia Europaea, IEEE Fellow, and ACL Fellow. He is President of the Association for Computational Linguistics (ACL) in 2025 and was President of the Asian Federation of Natural Language Processing (AFNLP) from 2019 to 2021. He won many awards such as the Second Prize of the National Scientific and Technological Progress Award of China, 2015, one of the most prestigious and influential awards in China.
Yang Zhao received the Ph.D. degree in pattern recognition and intelligent system from Institute of Automation, Chinese Academy of Sciences, China in 2019. He is currently an associate professor with the State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. His research interests include machine translation and natural language processing.
Yanjun Ma received the Ph.D. degree in computer science from Dublin City University in 2009. He currently serves as the General Manager of Baidu AI Platform & Ecosystem, overseeing the development of the open-source deep learning platform PaddlePaddle. His research focuses on natural language processing and deep learning, which is widely used in Baidu's products. Dr. Yanjun Ma has authored and co-authored over 20 research publications and served as the Area Co-Chair for a number of top international conferences. In 2015, Dr. Yanjun Ma received National Technology Advancement Award.
作者簡介(中文翻譯)
程青宗於1998年3月在中國科學院計算技術研究所獲得計算機科學博士學位。他目前是中國科學院自動化研究所的教授。他的研究興趣包括自然語言處理、機器翻譯和認知語言計算。他在頂級會議和期刊上發表了超過200篇論文。他是六本書的作者和合著者，其中包括於2021年與Springer出版的《文本數據挖掘》。他是歐洲科學院的成員，IEEE Fellow，以及ACL Fellow。他將於2025年擔任計算語言學會（ACL）會長，並於2019年至2021年擔任亞洲自然語言處理聯合會（AFNLP）會長。他獲得了許多獎項，例如2015年中國國家科技進步獎的二等獎，這是中國最具聲望和影響力的獎項之一。
楊兆於2019年在中國科學院自動化研究所獲得模式識別與智能系統博士學位。他目前是中國科學院自動化研究所多模態人工智慧系統國家重點實驗室的副教授。他的研究興趣包括機器翻譯和自然語言處理。
馬彥軍於2009年在都柏林城市大學獲得計算機科學博士學位。他目前擔任百度AI平台與生態系統的總經理，負責開源深度學習平台PaddlePaddle的開發。他的研究專注於自然語言處理和深度學習，這在百度的產品中被廣泛應用。馬彥軍博士已發表和合著超過20篇研究論文，並擔任多個頂級國際會議的區域共同主席。2015年，馬彥軍博士獲得國家科技進步獎。
