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Data Science for Supply Chain Forecasting (Paperback, 2nd ed.)
Loot Price: R1,241
Discovery Miles 12 410
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Data Science for Supply Chain Forecasting (Paperback, 2nd ed.)
Expected to ship within 12 - 17 working days
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Donate to Against Period Poverty
Total price: R1,261
Discovery Miles: 12 610
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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.
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