| 書(shū)目名稱(chēng) | Demand Prediction in Retail |
| 副標(biāo)題 | A Practical Guide to |
| 編輯 | Maxime C. Cohen,Paul-Emile Gras,Renyu Zhang |
| 視頻video | http://file.papertrans.cn/266/265041/265041.mp4 |
| 概述 | Covers 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 |
| 叢書(shū)名稱(chēng) | Springer Series in Supply Chain Management |
| 圖書(shū)封面 |  |
| 描述 | .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.. |
| 出版日期 | Textbook 2022 |
| 關(guān)鍵詞 | demand prediction; supply chain analytics; data-driven forecasting; predictive analytics; data science a |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-85855-1 |
| isbn_softcover | 978-3-030-85857-5 |
| isbn_ebook | 978-3-030-85855-1Series ISSN 2365-6395 Series E-ISSN 2365-6409 |
| issn_series | 2365-6395 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機(jī)版|小黑屋|
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