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Lingua: Inglese
Editore: Springer Nature Switzerland AG, CH, 2021
ISBN 10: 3030858545 ISBN 13: 9783030858544
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Aggiungi al carrelloHardback. Condizione: New. 2022 ed.
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Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 3030858545 ISBN 13: 9783030858544
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Aggiungi al carrelloCondizione: New. From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers.From data collection to evaluation and visualization of prediction results, this.
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture.This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.
Lingua: Inglese
Editore: Springer Nature Switzerland AG, CH, 2021
ISBN 10: 3030858545 ISBN 13: 9783030858544
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Aggiungi al carrelloHardcover. Condizione: Brand New. 172 pages. 9.25x6.10x1.26 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Springer International Publishing, Springer Nature Switzerland Dez 2021, 2021
ISBN 10: 3030858545 ISBN 13: 9783030858544
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture.This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy. 176 pp. Englisch.
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Aggiungi al carrelloBuch. Condizione: Neu. Demand Prediction in Retail | A Practical Guide to Leverage Data and Predictive Analytics | Maxime C. Cohen (u. a.) | Buch | Springer Series in Supply Chain Management | xvii | Englisch | 2021 | Springer | EAN 9783030858544 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: Springer, Springer Dez 2021, 2021
ISBN 10: 3030858545 ISBN 13: 9783030858544
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 117,69
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture.This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 176 pp. Englisch.