Machine Learning for Business Analytics : Concepts, Techniques and Applications with JMP Pro

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Machine Learning for Business Analytics : Concepts, Techniques and Applications with JMP Pro
Περιγραφή: 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.
Συγγραφείς: Galit Shmueli, Peter C. Bruce, Mia L. Stephens, Muralidhara Anandamurthy, Nitin R. Patel
Resource Type: eBook.
Θέματα: Data mining, Management--Data processing, Business mathematics--Computer programs, Business--Data processing
Categories: MATHEMATICS / Probability & Statistics / General, COMPUTERS / Data Science / Data Analytics
Βάση Δεδομένων: eBook Index
Περιγραφή
ISBN:9781119903833
9781119903840
9781119903857