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Guide to Industrial Analytics - Solving Data Science Problems for Manufacturing and the Internet of Things (Hardcover, 1st ed. 2021) Loot Price: R2,116
Discovery Miles 21 160
Guide to Industrial Analytics - Solving Data Science Problems for Manufacturing and the Internet of Things (Hardcover, 1st ed....

Guide to Industrial Analytics - Solving Data Science Problems for Manufacturing and the Internet of Things (Hardcover, 1st ed. 2021)

Richard Hill, Stuart Berry

Series: Texts in Computer Science

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Loot Price R2,116 Discovery Miles 21 160 | Repayment Terms: R198 pm x 12*

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This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: Texts in Computer Science
Release date: September 2021
First published: 2021
Authors: Richard Hill • Stuart Berry
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 275
Edition: 1st ed. 2021
ISBN-13: 978-3-03-079103-2
Categories: Books > Computing & IT > Internet > Network computers
Books > Computing & IT > Applications of computing > Computer modelling & simulation
Books > Professional & Technical > Mechanical engineering & materials > Production engineering > General
Books > Computing & IT > Applications of computing > Databases > Data mining
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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LSN: 3-03-079103-3
Barcode: 9783030791032

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