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Data science for supply chain forecasting

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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 (AI) & machine learning (ML) are not simply a question of coding skills. Using data science in order to solve a problem requires a scientific mindset more than coding skills. The story behind these models is one of experimentation, of observation and of constant questioning; a true scientific method must be applied to supply chain. In the data science field as well as that of the supply chain, simple questions do not come with simple answers. In order to resolve these questions, one needs to be both a scientist as well as to use the correct tools. In this book, we will discuss both. Is this Book for me? This book has been written for supply chain practitioners, forecasters and analysts who are looking to go the extra mile. You do not need technical IT skills to start using the models of this book. You do not need a dedicated server or expensive software licenses: you solely need your own computer. You do not need a PhD in mathematics: mathematics will only be utilized as a tool to tweak and understand the models. In the majority of the cases - especially when it comes to machine learning - a deep understanding of the mathematical inner workings of a model will not be necessary in order to optimize it and understand its limitations

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Ketersediaan

B20220712

658.702 VAN d

Pradita Library (600)

Tersedia

Informasi Detail

Judul Seri

-

No. Panggil

658.702 VAN d

Penerbit

Berlin : Walter de Gruyter., 2021

Deskripsi Fisik

xxviii, 282 hlm.; ilus.; 24 cm

Bahasa

English

ISBN/ISSN

9783110671100

Klasifikasi

600

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

2nd Edition

Subjek

Data science
Forecasting
Supply Chain

Info Detail Spesifik

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Pernyataan Tanggungjawab

-

Versi lain/terkait

Lampiran Berkas

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