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Condition: New. 2024th edition NO-PA16APR2015-KAP.
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Business Analytics With R and Python
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Business Analytics with R and Python (AI for Risks)
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Business Analytics With R and Python
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Business Analytics with R and Python
Published by Springer Verlag, Singapore, SG, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Language: English
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Add to basketHardback. Condition: New. 2024 ed. 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
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Business Analytics with R and Python
Published by Springer Verlag, Singapore, SG, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Language: English
Hardback. Condition: New. 2024 ed. 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
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Add to basketHardcover. Condition: Brand New. 206 pages. 9.25x6.10x9.21 inches. In Stock.
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Add to basketPaperback. Condition: Brand New. 206 pages. 9.25x6.10x9.25 inches. In Stock.
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Business Analytics with R and Python
Published by Springer, Berlin|Springer Nature Singapore|Springer, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Language: English
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Add to basketCondition: 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
Published by Springer Verlag, Singapore, SG, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Language: English
Hardback. Condition: New. 2024 ed. 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
Published by Springer Verlag, Singapore, SG, 2024
ISBN 10: 9819747716 ISBN 13: 9789819747719
Language: English
US$ 88.37
Convert currencyUS$ 87.70 shipping from United Kingdom to U.S.A.Quantity: 2 available
Add to basketHardback. Condition: New. 2024 ed. 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.
