Data Science for Supply Chain Forecasting
Author:   Nicolas Vandeput
Publisher:   De Gruyter
Edition:   2nd ed.
ISBN:  

9783110671100


Pages:   310
Publication Date:   22 March 2021
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Data Science for Supply Chain Forecasting


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Full Product Details

Author:   Nicolas Vandeput
Publisher:   De Gruyter
Imprint:   De Gruyter
Edition:   2nd ed.
Weight:   0.524kg
ISBN:  

9783110671100


ISBN 10:   3110671107
Pages:   310
Publication Date:   22 March 2021
Audience:   Professional and scholarly ,  Professional & Vocational ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

I Statistical Forecast Moving Average Forecast Error Exponential Smoothing Underfitting Double Exponential Smoothing Model Optimization Double Smoothing with Damped Trend Overfitting Triple Exponential Smoothing Outliers Triple Additive Exponential smoothing II Machine Learning Machine Learning Tree Parameter Optimization Forest Feature Importance Extremely Randomized Trees Feature Optimization Adaptive Boosting Exogenous Information & Leading Indicators Extreme Gradient Boosting Categories Clustering Glossary

Reviews

I had a chance to review the manuscript. It is a very good book. For the supply chain managers out there, you should read at least the first few chapters, and then have others on your team read the rest of it and act on it ... you can have close to state-of-the-art forecasts with a minimum of effort.... This book closes the coffin on vendors who are selling only a handful of forecasting models. --Joannes Vermorel, Founder and CEO, Lokad


Author Information

Nicolas Vandeput is a supply chain data scientist specialized in demand forecasting and inventory optimization. He founded his consultancy company SupChains in 2016 and co-founded SKU Science—a smart online platform for supply chain management—in 2018. He enjoys discussing new quantitative models and how to apply them to business reality. Passionate about education, Nicolas is both an avid learner and enjoys teaching at universities: he has taught forecasting and inventory optimization to master students since 2014 in Brussels, Belgium.

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