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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:
  • 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.

Machine Learning for Business Analytics: Concepts, Techniques and Applications

$112.00 Regular Price
$44.80Sale Price
    • Publisher ‏ : ‎ Wiley; 2nd edition (May 9, 2023)
    • Language ‏ : ‎ English
    • Hardcover ‏ : ‎ 608 pages
    • ISBN-10 ‏ : ‎ 1119903831
    • ISBN-13 ‏ : ‎ 978-1119903833
  • Peter C. Bruce

    Peter Bruce is the President and Founder of the Institute for Statistics Education at, a privately-owned online educational institution in Arlington, VA. Founded in 2002, the Institute specializes in introductory and graduate level online education in statistics, optimization, risk modeling, predictive modeling, data mining, and other subjects in quantitative analytics.

    Prior to founding, in partnership with the noted economist Julian Simon, Peter continued and commercialized the development of Simon's Resampling Stats, a tool for bootstrapping and resampling. In his work at Cytel Software Corp., he developed Box Sampler along similar lines, and helped bring XLMiner, a data mining add-in for Excel, to market. He has authored a number of journal articles in the area of resampling, and is a co-author (with Galit Shmueli and Nitin Patel) of "Data Mining for Business Intelligence"​ (Wiley, 2nd ed. 2010). He is also the author of "Introductory Statistics and Analytics"​ (Wiley, 2014). Early in his career, he co-authored (with D. Traynham) a noted review of airline deregulation in the National Review (May, 1980).

    Peter's role at the Institute centers on course development and faculty recruitment - there are over 60 faculty members from around the world who are published experts in their fields; most teach from their own texts. He also teaches a course on resampling methods.

    Peter has degrees in Russian from Princeton and Harvard, and an MBA from the University of Maryland; he is an autodidact in the area of statistics. Prior to his work in statistics, Peter worked in the US diplomatic corps as a Foreign Service Officer.

    Galit Shmueli

    Galit Shmueli is Distinguished Professor at the Institute of Service Science, National Tsing Hua University, Taiwan. She is also a visiting scholar at Academia Sinica's Institute of Statistical Science. Between 2011-2014 she was the SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics & Information Systems at the Indian School of Business. She is best known for her research and teaching in business analytics, with a focus on statistical and data mining methods for contemporary data and applications in information systems and healthcare.

    Dr. Shmueli's research has been published in the statistics, management, information systems, and marketing literature. She authored/co-authored over ninety journal articles, books, textbooks and book chapters, including the popular textbook Data Mining for Business Intelligence and Practical Time Series Forecasting. Dr. Shmueli is an award-winning teacher and speaker on data analytics.

    She has taught at Carnegie Mellon University, University of Maryland, the Israel Institute of Technology, and the Indian School of Business. Her experience spans business and engineering students and professionals, both online and on-ground. Dr. Shmueli teaches courses on data mining, statistics, forecasting, data visualization, and industrial statistics.

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