Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0

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Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0 is written by Lalitha Krishnasamy and published by Springer Nature. It's available with International Standard Book Number or ISBN identification 3031946375 (ISBN 10) and 9783031946370 (ISBN 13).

This book is a comprehensive resource that delves into the integration of advanced artificial intelligence techniques within the context of modern industrial practices. It systematically explores how distributed deep learning methodologies can be effectively combined with explainable AI to enhance transparency in Industry 4.0 applications. In recent years, neural networks and other deep learning models have produced remarkable outcomes in a variety of fields, including image recognition, natural language processing, and decision-making. Concerns have been raised regarding the transparency and interpretability of these models as a result of their increasing intricacy. The demand for methodologies and approaches associated with explainable artificial intelligence (XAI) has consequently increased. The primary aim of XAI is to enhance the transparency and comprehensibility of deep learning model decision-making processes for stakeholders, irrespective of their technical expertise.