Titlebook: Demand Prediction in Retail; A Practical Guide to Maxime C. Cohen,Paul-Emile Gras,Renyu Zhang Textbook 2022 The Editor(s) (if applicable) a

創(chuàng)作

Ines Gottschalk,Dilek Aysel Tepelics related to demand prediction, such as deep learning methods, transfer learning, and data censoring. For each topic, we provide a number of relevant references for interested readers. We close by discussing several decisions that can be guided by prescriptive analytics tools that rely on demand pr

闡明

Maxime C. Cohen,Paul-Emile Gras,Renyu ZhangCovers the entire process of demand prediction for any business setting.Discusses all the steps required in a real-world implementation.Includes additional material to assist the learning experience

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Textbook 2022 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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https://doi.org/10.1007/978-3-662-42497-1discuss the objective and scope considered in this book by elaborating on the concepts of training and test data, presenting several demand prediction accuracy metrics, and pinpointing the specific application under consideration.

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Introduction,discuss the objective and scope considered in this book by elaborating on the concepts of training and test data, presenting several demand prediction accuracy metrics, and pinpointing the specific application under consideration.

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