£128.20

Springer - Industrial AI: Applications with Sustainable Performance

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Description

Explore the emerging field of Industrial AI with this comprehensive guide from Springer. This book examines Industrial AI as a systematic discipline, focusing on the development, validation, and deployment of machine learning algorithms specifically designed for industrial applications. By prioritizing sustainable performance, the text provides a roadmap for integrating physical systems with advanced computational models. As the concept of Industrial AI is in its infancy, this resource prepares readers for a landscape that merges technologies like the Internet of Things (IoT) and Cyber-Physical Systems. The content explains how to combine state-of-the-art sensing, communication, and big data analytics platforms to create a cohesive methodology. Whether you are studying management through the lens of the Balanced Scorecard or looking to implement big data analytics in a professional setting, this book offers a deep dive into the integration of modern technology and industrial processes.

Key Features

Learn how to develop, validate, and deploy machine learning algorithms specifically for industrial applications and sustainable performance.

Understand the integration of physical systems with computational models through a systematic Industrial AI methodology.

Gain insights into the combined use of sensing, communication, and big data analytics platforms.

Explore the connection between Industrial AI and emerging technologies like the Internet of Things and Cyber-Physical Systems.

Study a discipline that is currently in its infancy to prepare for future industrial technological shifts.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
08 February 2020
Listed Since
12 November 2019

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No barcode data available

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