Data Science for Supply Chain Forecasting

Data Science for Supply Chain Forecasting by Nicolas Vandeput


ISBN
9783110671100
Published
Binding
Paperback
Pages
310
Dimensions
170 x 240mm

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.
EOFY 2025 Book Frenzy
84.14
RRP: $98.99
15% off RRP



Instore Price: $98.99
Enter your Postcode or Suburb to view availability and delivery times.

Other Titles by Nicolas Vandeput

Inventory Optimization
92.99
79.04
15% Off

You might also like


RRP refers to the Recommended Retail Price as set out by the original publisher at time of release.
The RRP set by overseas publishers may vary to those set by local publishers due to exchange rates and shipping costs.
Due to our competitive pricing, we may have not sold all products at their original RRP.