Data Science for Supply Chain Forecasting is popular PDF and ePub book, written by Nicolas Vandeput in 2021-03-22, it is a fantastic choice for those who relish reading online the Business & Economics genre. Let's immerse ourselves in this engaging Business & Economics book by exploring the summary and details provided below. Remember, Data Science for Supply Chain Forecasting can be Read Online from any device for your convenience.
Data Science for Supply Chain Forecasting Book PDF Summary
Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a true scientific method which includes experimentation, observation, and constant questioning must be applied to supply chains to achieve excellence in demand forecasting. This second edition adds more than 45 percent extra content with four new chapters including an introduction to neural networks and the forecast value added framework. Part I focuses on statistical "traditional" models, Part II, on machine learning, and the all-new Part III discusses demand forecasting process management. The various chapters focus on both forecast models and new concepts such as metrics, underfitting, overfitting, outliers, feature optimization, and external demand drivers. The book is replete with do-it-yourself sections with implementations provided in Python (and Excel for the statistical models) to show the readers how to apply these models themselves. This hands-on book, covering the entire range of forecasting—from the basics all the way to leading-edge models—will benefit supply chain practitioners, forecasters, and analysts looking to go the extra mile with demand forecasting.
Detail Book of Data Science for Supply Chain Forecasting PDF
- Author : Nicolas Vandeput
- Release : 22 March 2021
- Publisher : Walter de Gruyter GmbH & Co KG
- ISBN : 9783110671124
- Genre : Business & Economics
- Total Page : 310 pages
- Language : English
- PDF File Size : 10,8 Mb
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