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Hardcover. Condition: Good. May contain highlighting/underlining/notes/etc. May have used stickers on cover. Access codes and supplements are not guaranteed to be included with used books. Ships same or next day. Expedited shipping: 3-5 business days, Standard shipping: 4-14 business days.
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Data Mining for Business Analytics: Concepts, Techniques, and Applications in R
Published by Wiley
ISBN 10: 1118879368 ISBN 13: 9781118879368
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Machine Learning for Business Analytics : Concepts, Techniques, and Applications in R
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Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R
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Machine Learning for Business Analytics : Concepts, Techniques, and Applications in R
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Machine Learning for Business Analytics
Language: English
Published by John Wiley and Sons Inc, US, 2023
ISBN 10: 1119835178 ISBN 13: 9781119835172
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning -also known as data mining or data analytics- is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using RAn expanded chapter focused on discussion of deep learning techniquesA new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniquesEnd-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presentedA companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.
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Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R, Second Edition
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Add to basketHardcover. Condition: Brand New. 2nd edition. 672 pages. 10.28x7.20x1.18 inches. In Stock.
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Machine Learning for Business Analytics
Language: English
Published by John Wiley and Sons Inc, US, 2023
ISBN 10: 1119835178 ISBN 13: 9781119835172
US$ 177.85
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Add to basketHardback. Condition: New. MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning -also known as data mining or data analytics- is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using RAn expanded chapter focused on discussion of deep learning techniquesA new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniquesEnd-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presentedA companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.
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Data Mining for Business Analytics: Concepts, Tech niques, and Applications in R
Language: English
Published by John Wiley & Sons Inc, 2017
ISBN 10: 1118879368 ISBN 13: 9781118879368
US$ 255.93
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Add to basketHardcover. Condition: Brand New. har/psc edition. 544 pages. 11.00x8.00x1.25 inches. In Stock.
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Data Mining for Business Analytics: Concepts, Techniques, and Applications in R
Published by John Wiley & Sons Inc
hardcover. Condition: LikeNew. Pages are New and Unused, Front or Back cover is damaged- torn, wrinkled or dented., Used Like New, no missing pages, no damage to binding, may have a remainder mark.
