Data Science For Supply Chain Forecasting

Author: Nicolas Vandeput
Editor: Walter de Gruyter GmbH & Co KG
ISBN: 3110671123
File Size: 36,55 MB
Format: PDF, ePub, Docs
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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.
Data Science for Supply Chain Forecasting
Language: en
Pages: 310
Authors: Nicolas Vandeput
Categories: Business & Economics
Type: BOOK - Published: 2021-03-22 - Publisher: Walter de Gruyter GmbH & Co KG

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.
Data Science for Supply Chain Forecast
Language: en
Pages: 237
Authors: Nicolas Vandeput
Categories: Business & Economics
Type: BOOK - Published: 2018-11-12 - Publisher: Independently Published

Data Science for Supply Chain Forecast Data Science for Supply Chain Forecast is a book for practitioners focusing on data science and machine learning; it demonstrates how both are closely interlinked in order to create an advanced forecast for supply chain. As one will discover in this book, artificial intelligence
Big Data Driven Supply Chain Management
Language: en
Pages: 262
Authors: Nada R. Sanders
Categories: Business & Economics
Type: BOOK - Published: 2014 - Publisher: Pearson Education

Master a complete, five-step roadmap for leveraging Big Data and analytics to gain unprecedented competitive advantage from your supply chain. Using Big Data, pioneers such as Amazon, UPS, and Wal-Mart are gaining unprecedented mastery over their supply chains. They are achieving greater visibility into inventory levels, order fulfillment rates, material
Supply Chain Management Strategies and Risk Assessment in Retail Environments
Language: en
Pages: 351
Authors: Kumar, Akhilesh, Saurav, Swapnil
Categories: Business & Economics
Type: BOOK - Published: 2017-12-15 - Publisher: IGI Global

The proper understanding and managing of project risks and uncertainties is crucial to any organization. It is paramount that all phases of project development and execution are monitored to avoid poor project results from meager economics, overspending, and reputation. Supply Chain Management Strategies and Risk Assessment in Retail Environments is
Inventory Optimization
Language: en
Pages: 318
Authors: Nicolas Vandeput
Categories: Business & Economics
Type: BOOK - Published: 2020-08-24 - Publisher: Walter de Gruyter GmbH & Co KG

In this book . . . Nicolas Vandeput hacks his way through the maze of quantitative supply chain optimizations. This book illustrates how the quantitative optimization of 21st century supply chains should be crafted and executed. . . . Vandeput is at the forefront of a new and better way