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9789819747719 - Business Analytics With R and Python di Olson, David L.; Wu, Desheng Dash; Luo, Cuicui; Nabavi, Majid (24 risultati)
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Business Analytics with R and Python (AI for Risks)
Da: Marlton Books, Bridgeton, NJ, U.S.A.
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Condizione: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. hardcover Used - Acceptable 2024.
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Business Analytics with R and Python (Hardcover)
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: new. Hardcover. This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, descriptive analytics focuses on what has happened and predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 3 describes initial data visualization tools. Chapter 4 describes association rules and software support. Chapter 5 describes cluster analysis with software demonstration. Chapter 6 discusses time series analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Applications of the context of management are presented in Chapter 8. Chapter 9 covers prescriptive modeling in business and applications of artificial intelligence. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 5 describes cluster analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Business Analytics With R and Python
Da: GreatBookPrices, Columbia, MD, U.S.A.
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Business Analytics with R and Python
Lingua: Inglese
Editore: Springer Verlag, Singapore, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Da: PBShop.store US, Wood Dale, IL, U.S.A.
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Business Analytics with R and Python
Lingua: Inglese
Editore: Springer Verlag, Singapore, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
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Business Analytics With R and Python
Da: GreatBookPrices, Columbia, MD, U.S.A.
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Business Analytics With R and Python
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Business Analytics with R and Python
Lingua: Inglese
Editore: Springer Verlag, Singapore, SG, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
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Aggiungi al carrelloHardback. Condizione: New. 2024 ed.
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Business Analytics with R and Python (AI for Risks)
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Business Analytics with R and Python (AI for Risks)
Da: Chiron Media, Wallingford, Regno Unito
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Aggiungi al carrellohardcover. Condizione: New.
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Business Analytics With R and Python
Da: Books Puddle, New York, NY, U.S.A.
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Condizione: New. 2024th edition NO-PA16APR2015-KAP.
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Business Analytics With R and Python
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Business Analytics with R and Python (AI for Risks)
Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Brand New. 206 pages. 9.25x6.10x9.21 inches. In Stock.
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Business Analytics With R and Python
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Business Analytics With R and Python
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Business Analytics with R and Python (AI for Risks)
Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Brand New. 206 pages. 9.25x6.10x9.21 inches. In Stock.
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Business Analytics with R and Python
Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Singapore|Springer, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
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Aggiungi al carrelloCondizione: New. This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, d.
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Business Analytics with R and Python (Hardcover)
Lingua: Inglese
Editore: Springer Verlag, Singapore, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Da: AussieBookSeller, Truganina, VIC, Australia
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, descriptive analytics focuses on what has happened and predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 3 describes initial data visualization tools. Chapter 4 describes association rules and software support. Chapter 5 describes cluster analysis with software demonstration. Chapter 6 discusses time series analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Applications of the context of management are presented in Chapter 8. Chapter 9 covers prescriptive modeling in business and applications of artificial intelligence. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 5 describes cluster analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Business Analytics with R and Python
Lingua: Inglese
Editore: Springer Nature Singapore Jul 2024, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware -This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, descriptive analytics focuses on what has happened and predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 3 describes initial data visualization tools. Chapter 4 describes association rules and software support. Chapter 5 describes cluster analysis with software demonstration. Chapter 6 discusses time series analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Applications of the context of management are presented in Chapter 8. Chapter 9 covers prescriptive modeling in business and applications of artificial intelligence.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 208 pp. Englisch.
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Business Analytics with R and Python
Lingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
EUR 69,56
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, descriptive analytics focuses on what has happened and predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 3 describes initial data visualization tools. Chapter 4 describes association rules and software support. Chapter 5 describes cluster analysis with software demonstration. Chapter 6 discusses time series analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Applications of the context of management are presented in Chapter 8. Chapter 9 covers prescriptive modeling in business and applications of artificial intelligence.
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Business Analytics with R and Python
Lingua: Inglese
Editore: Springer Verlag, Singapore, SG, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Da: Rarewaves.com UK, London, Regno Unito
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Aggiungi al carrelloBuch. Condizione: Neu. Business Analytics with R and Python | David L. Olson (u. a.) | Buch | x | Englisch | 2024 | Springer | EAN 9789819747719 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Business Analytics with R and Python
Lingua: Inglese
Editore: Springer Verlag, Singapore Sep 2024, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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EUR 69,54
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, descriptive analytics focuses on what has happened and predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 3 describes initial data visualization tools. Chapter 4 describes association rules and software support. Chapter 5 describes cluster analysis with software demonstration. Chapter 6 discusses time series analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Applications of the context of management are presented in Chapter 8. Chapter 9 covers prescriptive modeling in business and applications of artificial intelligence. 196 pp. Englisch.
