Unlocking Artificial Intelligence
From Theory to Applications
Contributor(s)
Mutschler, Christopher (editor)
Münzenmayer, Christian (editor)
Uhlmann, Norman (editor)
Martin, Alexander (editor)
Language
EnglishAbstract
This open access book provides a state-of-the-art overview of current machine learning research and its exploitation in various application areas. It has become apparent that the deep integration of artificial intelligence (AI) methods in products and services is essential for companies to stay competitive. The use of AI allows large volumes of data to be analyzed, patterns and trends to be identified, and well-founded decisions to be made on an informative basis. It also enables the optimization of workflows, the automation of processes and the development of new services, thus creating potential for new business models and significant competitive advantages. The book is divided in two main parts: First, in a theoretically oriented part, various AI/ML-related approaches like automated machine learning, sequence-based learning, deep learning, learning from experience and data, and process-aware learning are explained. In a second part, various applications are presented that benefit from the exploitation of recent research results. These include autonomous systems, indoor localization, medical applications, energy supply and networks, logistics networks, traffic control, image processing, and IoT applications. Overall, the book offers professionals and applied researchers an excellent overview of current exploitations, approaches, and challenges of AI/ML-related research.
Keywords
machine learning; time-series analysis; artificial intelligence; data annotation; logistics and transportation applications; healthcare informatics; geographical information systemsDOI
10.1007/978-3-031-64832-8ISBN
9783031648328, 9783031648311, 9783031648328Publisher
Springer NaturePublisher website
https://www.springernature.com/gp/products/booksPublication date and place
Cham, 2024Imprint
Springer Nature SwitzerlandClassification
Machine learning
Applied computing