Machine Learning for Business Analytics
eBook - PDF

Machine Learning for Business Analytics

Concepts, Techniques and Applications with JMP Pro

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Machine Learning for Business Analytics

Concepts, Techniques and Applications with JMP Pro

About this book

MACHINE LEARNING FOR BUSINESS ANALYTICS

An up-to-date introduction to a market-leading platform for data analysis and machine learning

Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. offers an accessible and engaging introduction to machine learning. It provides concrete examples and case studies to educate new users and deepen existing users' understanding of their data and their business. Fully updated to incorporate new topics and instructional material, this remains the only comprehensive introduction to this crucial set of analytical tools specifically tailored to the needs of businesses.

Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. readers will also find:

  • Updated material which improves the book's usefulness as a reference for professionals beyond the classroom
  • Four new chapters, covering topics including Text Mining and Responsible Data Science
  • An updated companion website with data sets and other instructor resources: www.jmp.com/dataminingbook
  • A guide to JMP Pro's new features and enhanced functionality

Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. is ideal for students and instructors of business analytics and data mining classes, as well as data science practitioners and professionals in data-driven industries.

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

Information

Publisher
Wiley
Year
2023
Print ISBN
9781119903833
eBook ISBN
9781119903840
Edition
2
Subtopic
Data Mining

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Contents
  5. Foreword
  6. Preface
  7. Acknowledgments
  8. PART I PRELIMINARIES
  9. PART II DATA EXPLORATION ANDDIMENSION REDUCTION
  10. PART III PERFORMANCE EVALUATION
  11. PART IV PREDICTION AND CLASSIFICATION METHODS
  12. PART V INTERVENTION AND USER FEEDBACK
  13. PART VI MINING RELATIONSHIPS AMONG RECORDS
  14. PART VII FORECASTING TIME SERIES
  15. PART VIII DATA ANALYTICS
  16. PART IX CASES
  17. References
  18. Data Files Used in the Book
  19. Index