Vendeur : BooksRun, Philadelphia, PA, Etats-Unis
EUR 43,97
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Ajouter au panierHardcover. Etat : Good. 2. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
Vendeur : Dream Books Co., Denver, CO, Etats-Unis
EUR 44,44
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : acceptable. This copy has clearly been enjoyedâ"expect noticeable shelf wear and some minor creases to the cover. Binding is strong, and all pages are legible. May contain previous library markings or stamps.
Vendeur : SellOnline2020, PLAISTOW, NH, Etats-Unis
EUR 59,22
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Ajouter au panierHardcover. Etat : New. 2nd Edition. Brand New US Edition textbook. Ship from Multiple Locations, including Asia , Hong Kong ,Taiwan , US or Canada depend on stock location.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 88,36
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Ajouter au panierEtat : New.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 103,27
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : Books Puddle, New York, NY, Etats-Unis
EUR 125,54
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Ajouter au panierEtat : New.
Vendeur : ALLBOOKS1, Direk, SA, Australie
EUR 130,25
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Ajouter au panierBrand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 116,32
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Ajouter au panierEtat : New.
Vendeur : Majestic Books, Hounslow, Royaume-Uni
EUR 132,05
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Ajouter au panierEtat : New.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 127,30
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Ajouter au panierEtat : New. In.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 114,88
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Ajouter au panierHardcover. Etat : Brand New. 2nd edition. 672 pages. 10.28x7.20x1.18 inches. In Stock.
Vendeur : Chiron Media, Wallingford, Royaume-Uni
EUR 125,06
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Ajouter au panierHardcover. Etat : New.
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
EUR 133,85
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Ajouter au panierEtat : New.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 136,15
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Ajouter au panierEtat : As New. Unread book in perfect condition.
EUR 108
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Ajouter au panierEtat : NEW.
Vendeur : Mooney's bookstore, Den Helder, Pays-Bas
EUR 140,37
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Ajouter au panierEtat : Very good.
Edité par John Wiley and Sons Inc, US, 2023
ISBN 10 : 1119835178 ISBN 13 : 9781119835172
Langue: anglais
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
EUR 183,61
Autre deviseQuantité disponible : 10 disponible(s)
Ajouter au panierHardback. Etat : 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.
Vendeur : Ubiquity Trade, Miami, FL, Etats-Unis
EUR 224,88
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. Brand new! Please provide a physical shipping address.
Edité par John Wiley and Sons Inc, US, 2023
ISBN 10 : 1119835178 ISBN 13 : 9781119835172
Langue: anglais
Vendeur : Rarewaves.com UK, London, Royaume-Uni
EUR 172,36
Autre deviseQuantité disponible : 10 disponible(s)
Ajouter au panierHardback. Etat : 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.