Vandeput, Nicolas
Data Science for Supply Chain Forecasting
- ISBN 13:
- 9783110671100
- author:
- Vandeput, Nicolas
- format:
- Paperback
- publisher:
- De Gruyter
- language:
- English
- Publication Year:
- 2019
- Pages:
- 280
- Dimensions:
- 24 x 17 centimeters (0.40 kg)
- Genre:
- Business, Leadership, Business,
- Condition:
- New
- Availability:
- Item usually sent within 2 working days
Description
Data Science for Supply Chain Forecasting by Nicolas Vandeput is a comprehensive guide to applying scientific methods to improve demand forecasting in supply chains. The book explores traditional statistical models, machine learning, and new concepts such as metrics, underfitting, and feature optimization, providing hands-on implementations in Python and Excel. With its focus on experimentation, observation, and constant questioning, this book offers a unique approach to achieving excellence in supply chain forecasting. The second edition includes four new chapters, covering topics such as neural networks and the forecast value added framework, and provides over 45% extra content. Suitable for supply chain practitioners, forecasters, and analysts, this book provides a thorough understanding of the entire range of forecasting methods, from basics to leading-edge models.
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