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Nachrichten, Termine, Experten
Nachrichten, Termine, Experten
Over the past three decades, Machine Learning has permeated the optimization of production processes, material and machine design and can now be found everywhere in industrial practice. It is therefore important for industry professionals to develop a basic understanding of it. Prof. Dr. Anita Schöbel, Director of the Fraunhofer Institute for Industrial Mathematics ITWM, and Prof. Dr. Jürgen Franke from the University of Kaiserslautern-Landau (RPTU), have published the book »Statistical Machine Learning for Engineering with Applications«, which provides an accessible introduction to the concepts and methods of Machine Learning.
The aim of this introduction to Machine Learning is to familiarize readers with fundamental topics such as classification trees, Bayesian learning, neural networks and deep learning. The individual contributions pay particular attention to the application and interpretation of these methods in practice, largely avoiding mathematical and algorithmic details.
Close to Practice With Case Studies From the Industry
The book contains several detailed case studies based on real industrial projects. These cover a wide range of technical applications, from vehicle construction to process and materials engineering to the optimization of production processes through image analysis. In concrete terms, for example, they deal with the deformation of cable bundles, the detection of cracks in concrete, fraud detection in the care sector through the automated evaluation of invoices or the prediction of breakthrough curves in reactive porous media.
Overall, the book focuses on the fundamental ideas, practical applicability and challenges of Machine Learning in industry and science. With only a very basic knowledge of statistics as a prerequisite, this book is a valuable resource for anyone looking to enter the world of Machine Learning.
Three Questions to Prof. Dr. Jürgen Franke
In the interview, Prof. Dr. Jürgen Franke summarizes the special features of the book.
Who should definitely read the book?
Our book is aimed at people from the natural sciences or engineering in practice who want to get a brief and easy-to-understand overview of Machine Learning and its use in real industrial projects. It is also a worthwhile read for students of the relevant disciplines who want a quick introduction to the field and an impression of real applications.
Why should these people read the book?
In scientific or engineering professions, it is useful to have a basic understanding of these processes – especially for smooth communication with experts who are called in to help solve problems. In addition, with the necessary basic knowledge, you can better judge how much promises made by people who want to sell you a finished tool are worth.
What do you think is unique about the book?
The combination of a fairly short introduction, but which includes many Machine Learning methods and focuses on the interpretation of results and limits of applicability, and a collection of real industry case studies covering a wide range of applications.
Prof. Dr. Anita Schöbel
Director of the Fraunhofer ITWM
Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM
Fraunhofer-Platz 1
67663 Kaiserslautern
Statistical Machine Learning for Engineering with Applications
herausgegeben von
Jürgen Franke
Anita Schöbel
Copyright-Jahr
2024
Verlag
Springer Nature Switzerland
Electronic ISBN
978-3-031-66253-9
Print ISBN
978-3-031-66252-2
DOI
https://doi.org/10.1007/978-3-031-66253-9
https://www.itwm.fraunhofer.de/en/press-publications/press-releases/2025/2025_03...
Criteria of this press release:
Business and commerce, Journalists, Students
Electrical engineering, Materials sciences, Mathematics, Mechanical engineering
transregional, national
Scientific Publications
English
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