"This book brings machine learning techniques to the IIoT community through a story that is able to be understood and applied by engineers and practitioners traditionally distanced from these techniques. Testbeds fuel the advancement of the IIoT with results from real-world data that can be applied to showcase machine learning capabilities. This book provides a clear description of how data is managed through an IIoT architecture and demonstrates the power of testbeds."
—Dr. Richard Soley, Executive Director, Industrial Internet Consortium (IIC)
"The Machine Learning techniques presented in this highly relevant publication provide an excellent overview of key areas critical to know about when implementing those fundamentally renewed algorithms that are driving the Fourth Industrial Revolution. Using real world IIoT applications, this book presents a clear description of sensor fusion and machine learning analytics technologies, where programmable logic and other hardware technologies play a central role in the data acquisition, analysis, and transformation implementations to realize actionable insights through real world IIoT applications described in this book."
—Christoph Fritsch, Senior Director Industrial IoT, Scientific and Medical Business Unit, Xilinx Inc.
"This book fills a gap in the current technological developments presenting the most extensive and in-depth analysis of machine learning methods for industrial applications. It is very well written and organized with special focus on professional, researchers and post-graduate students of both industrial engineering and machine learning."
—Associate Professor Joao Gama, Porto University
Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problems in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. As such, it should be of special interest to researchers interested in real-world industrial problems.
