Machine Learning for Business Analytics: Concepts, Techniques and Applications in Rapidminer (Hardcover)
暫譯: 商業分析的機器學習:Rapidminer中的概念、技術與應用 (精裝版)

Shmueli, Galit, Bruce, Peter C., Deokar, Amit V.

  • 出版商: Wiley
  • 出版日期: 2023-03-08
  • 售價: $6,640
  • 貴賓價: 9.5$6,308
  • 語言: 英文
  • 頁數: 736
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1119828791
  • ISBN-13: 9781119828792
  • 相關分類: Machine Learning
  • 海外代購書籍(需單獨結帳)

商品描述

Machine Learning for Business Analytics

Machine learning--also known as data mining or data analytics--is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information.

Machine Learning for Business Analytics: Concepts, Techniques and Applications in RapidMiner provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques.

This is the seventh edition of Machine Learning for Business Analytics, and the first using RapidMiner software. This edition also includes:

  • A new co-author, Amit Deokar, who brings experience teaching business analytics courses using RapidMiner
  • Integrated use of RapidMiner, an open-source machine learning platform that has become commercially popular in recent years
  • An expanded chapter focused on discussion of deep learning techniques
  • A new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learning
  • A new chapter on responsible data science
  • Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students
  • A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques
  • End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented
  • A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions

This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.

商品描述(中文翻譯)

**商業分析的機器學習**

**機器學習——也稱為資料挖掘或資料分析——是資料科學的基本組成部分。它被各種組織用於將原始資料轉化為可行的資訊。**

*《商業分析的機器學習:概念、技術與RapidMiner中的應用》* 提供了對這一方法論的全面介紹和概述。這本暢銷教科書涵蓋了預測、分類、視覺化、降維、規則挖掘、推薦、聚類、文本挖掘、實驗和網絡分析的統計和機器學習算法。除了實作練習和真實案例研究外,它還討論了負責任使用機器學習技術的管理和倫理問題。

這是*《商業分析的機器學習》*的第七版,也是第一個使用RapidMiner軟體的版本。本版還包括:

- 新的共同作者Amit Deokar,他在使用RapidMiner教授商業分析課程方面具有經驗
- 整合使用RapidMiner,這是一個在近年來變得商業上受歡迎的開源機器學習平台
- 擴展的章節,專注於深度學習技術的討論
- 新的章節,介紹實驗反饋技術,包括A/B測試、提升建模和強化學習
- 新的章節,關於負責任的資料科學
- 根據教授MBA、商業分析碩士及相關課程的講師和他們的學生的反饋更新和新增的材料
- 一整章專門介紹相關案例研究,包含十多個案例展示機器學習技術的應用
- 章末練習,幫助讀者評估和擴展對所呈現材料的理解和能力
- 一個伴隨網站,提供二十多個資料集,以及包括練習解答、簡報和案例解答的講師材料

這本教科書是高年級本科生和研究生資料科學、預測分析和商業分析課程的理想資源。它也是分析師、研究人員和資料科學從業者在管理、金融、行銷、運營管理、資訊系統、計算機科學和資訊技術等領域處理定量資料的優秀參考資料。

作者簡介

Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University's Institute of Service Science, College of Technology Management. She has designed and instructed business analytics courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan.

Peter C. Bruce, is Founder of the Institute for Statistics Education at Statistics.com, and Chief Learning Officer at Elder Research, Inc.

Amit V. Deokar, PhD, is Associate Dean of Undergraduate Programs and an Associate Professor of Management Information Systems at the Manning School of Business at University of Massachusetts Lowell. Since 2006, he has developed and taught courses in business analytics, with expertise in using the RapidMiner platform. He is an Association for Information Systems Distinguished Member Cum Laude.

Nitin R. Patel, PhD, is cofounder and lead researcher at Cytel Inc. He was also a co-founder of Tata Consultancy Services. A Fellow of the American Statistical Association, Dr. Patel has served as a visiting professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad, for 15 years.

作者簡介(中文翻譯)

Galit Shmueli, PhD, 是國立清華大學服務科學研究所的特聘教授,隸屬於科技管理學院。自2004年以來,她在馬里蘭大學、Statistics.com、印度商學院及國立清華大學(台灣)設計並教授商業分析課程。

Peter C. Bruce, 是Statistics.com統計教育研究所的創始人,並擔任Elder Research, Inc.的首席學習官。

Amit V. Deokar, PhD, 是麻省大學洛威爾分校曼寧商學院本科項目的副院長及管理資訊系統的副教授。自2006年以來,他開發並教授商業分析課程,專長於使用RapidMiner平台。他是資訊系統協會的榮譽會員。

Nitin R. Patel, PhD, 是Cytel Inc.的共同創辦人及首席研究員。他也是塔塔顧問服務公司的共同創辦人。作為美國統計協會的會士,Patel博士曾在麻省理工學院和哈佛大學擔任訪問教授。他是印度計算機學會的會士,並在印度管理學院艾哈邁達巴德任教15年。