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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 focused on the development, validation, and deployment of machine learning algorithms designed for industrial applications. By integrating state-of-the-art sensing, communication, and big data analytics platforms, the text explains how a systematic methodology enables the integration of physical systems with computational models. As the concept of Industrial AI is in its infancy, this work covers essential technologies that shape the field, including the Internet of Things and Cyber-Physical Systems. It provides a multi-dimensional look at how these technologies work together to achieve sustainable performance in industrial environments.

Key Features

This Springer publication introduces Industrial AI as a systematic discipline for industrial applications.

Learn to develop, validate, and deploy various machine learning algorithms for sustainable performance.

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

Explore the connection between sensing, communication, and big data analytics platforms.

Gain insights into emerging technologies like the Internet of Things and Cyber-Physical Systems.

Product Specifications

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

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