Machine Learning for Business Analytics

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A01=Galit Shmueli
A01=Mia L. Stephens
A01=Muralidhara Anandamurthy
A01=Nitin R. Patel
A01=Peter C. Bruce
Age Group_Uncategorized
Age Group_Uncategorized
algorithms
artificial intelligence
Author_Galit Shmueli
Author_Mia L. Stephens
Author_Muralidhara Anandamurthy
Author_Nitin R. Patel
Author_Peter C. Bruce
automatic-update
business analytics
Category1=Non-Fiction
Category=PB
classification
clustering
COP=United States
Data analysis
data mining
data science
Delivery_Delivery within 10-20 working days
dimension reduction
eq_isMigrated=2
eq_nobargain
JMP Pro predictive modeling
JMP Pro(R)
JMP Pro®
Language_English
PA=Not available (reason unspecified)
prediction
predictive modeling
Price_€100 and above
PS=Active
recommendations
responsible data science
softlaunch
text mining
time series forecasting

Product details

  • ISBN 9781119903833
  • Weight: 1338g
  • Dimensions: 185 x 257mm
  • Publication Date: 17 Apr 2023
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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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.

Galit Shmueli, PhD is Distinguished Professor at National Tsing Hua University's Institute of Service Science. 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.

Mia L. Stephens, M.S. is an Advisory Product Manager with JMP, driving the product vision and roadmaps for JMP and JMP Pro.

Muralidhara Anandamurthy, PhD is an Academic Ambassador with JMP, overseeing technical support for academic users of JMP Pro.

Nitin R. Patel, PhD is cofounder and lead researcher at Cytel Inc. He is also a Fellow of the American Statistical Association and has served as a visiting professor at the Massachusetts Institute of Technology and Harvard University, among others.

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