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Machine Learning for Business Analytics: Concepts, Techniques and Applications with JMP Pro 2nd Edition, e-book

byGoodEBook
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Hello, welcome to Goodebook!!!

**This is an instant download PDF. No Physical item will be shipped**

♥ ♥ After downloading, you will receive a PDF File


About this item
  • Hight Quality PDF /EPUB format
  • Digital E-books
  • Instant Download
  • Lifetime Access
  • ISBN-10: ‎ 1119903831
  • ISBN-13:  978-1119903833

COMPATIBLE DEVICES:
Version: PDF. It can be permanently stored and read on any device

QUALITY:
High Quality. No missing contents. Printable.

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The Download Link will be automatically sent to your Email immediately after you complete the payment.

Description:

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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Listed on 4 June, 2024