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Demand Prediction in Retail

A Practical Guide to Leverage Data and Predictive Analytics

By: Maxime C. Cohen,Paul-Emile Gras,Arthur Pentecoste,Renyu Zhang

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Demand Prediction in Retail

A Practical Guide to Leverage Data and Predictive Analytics

By: Maxime C. Cohen,Paul-Emile Gras,Arthur Pentecoste,Renyu Zhang

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.

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Page Count

166

Publisher

Springer Nature

Published Date

ISBN 10

3030858553

ISBN 13

9783030858551

Demand Prediction in Retail

A Practical Guide to Leverage Data and Predictive Analytics

By: Maxime C. Cohen,Paul-Emile Gras,Arthur Pentecoste,Renyu Zhang

Write a review Read reviews Take a Quiz Solve Book Puzzle

Demand Prediction in Retail

A Practical Guide to Leverage Data and Predictive Analytics

By: Maxime C. Cohen,Paul-Emile Gras,Arthur Pentecoste,Renyu Zhang

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.

Average ratings

N/A

5

0%

4

0%

3

0%

2

0%

1

0%

Solve jigsaw puzzle

Age

Page Count

166

Publisher

Springer Nature

Published Date

ISBN 10

3030858553

ISBN 13

9783030858551