Data Science for Supply Chain Forecasting
Nicolas is a Data Scientist in Supply Chain who specializes in Demand Forecasting and Inventory Optimization. He is always excited to talk about new quantitative models and how to apply them to business reality. Nicolas is an avid learner and enjoys teaching at colleges such as the University of Brussels, where he has taught forecasting and inventory optimization to master students since 2014. In 2016, he founded SupChains, then in 2018, he co-launched SKU Science, a smart online platform for supply chain management.
Using data science to tackle an issue necessitates a scientific mentality in addition to coding abilities. Data Science for Supply Chain Forecasting, Second Edition believes that in order to attain perfection in demand forecasting, supply networks must employ a truly scientific technique that incorporates experimentation, observation, and persistent questioning.
This second version of Data Science for Supply Chain Forecasting includes four additional chapters, including an introduction to neural networks and the forecast value added framework, which adds more than 45 percent more content. Part I focuses on statistical "conventional" models, Part II on machine learning, and Part III on the revolutionary Part III examines the management of the demand forecasting process. The chapters cover forecast models as well as novel ideas including metrics, underfitting, overfitting, outliers, feature optimization, and external demand factors. The book is full with do-it-yourself sections with Python implementations (and Excel for the statistical models) to demonstrate readers how to apply these models themselves.
This hands-on book, which covers the whole spectrum of forecasting—from the fundamentals to cutting-edge models—will assist supply chain practitioners, forecasters, and analysts wishing to go above and beyond with demand forecasting. The book is regarded as one of the best books on supply chain management.
Author: Nicolas Vandeput
Link to buy: https://www.amazon.com/dp/3110671107
Ratings: 4.6 out of 5 stars (from 54 reviews)
Best Sellers Rank: #186,764 in Books
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