Machine Learning for Business Analytics
eBook - ePub

Machine Learning for Business Analytics

Concepts, Techniques and Applications in RapidMiner

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Machine Learning for Business Analytics

Concepts, Techniques and Applications in RapidMiner

About this book

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.

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Yes, you can access Machine Learning for Business Analytics by Galit Shmueli,Peter C. Bruce,Amit V. Deokar,Nitin R. Patel in PDF and/or ePUB format, as well as other popular books in Computer Science & Data Mining. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2023
Print ISBN
9781119828792
eBook ISBN
9781119828815

Table of contents

  1. Cover
  2. Table of Contents
  3. Title Page
  4. Copyright
  5. Dedication
  6. Foreword by Ravi Bapna
  7. Preface to the RapidMiner Edition
  8. Acknowledgments
  9. PART I: Preliminaries
  10. PART II: Data Exploration and Dimension Reduction
  11. PART III: Performance Evaluation
  12. PART IV: Prediction and Classification Methods
  13. PART V: Intervention and User Feedback
  14. PART VI: Mining Relationships Among Records
  15. PART VII: Forecasting Time Series
  16. PART VIII: Data Analytics
  17. PART IX: Cases
  18. References
  19. Data Files Used in the Book
  20. Index
  21. End User License Agreement