Description

Book Synopsis
Machine learning and artificial intelligence are ubiquitous terms for improving technical processes. However, practical implementation in real-world problems is often difficult and complex. This textbook explains learning methods based on analytical concepts in conjunction with complete programming examples in Python, always referring to real technical application scenarios. It demonstrates the use of physics-informed learning strategies, the incorporation of uncertainty into modeling, and the development of explainable, trustworthy artificial intelligence with the help of specialized databases. Therefore, this textbook is aimed at students of engineering, natural science, medicine, and business administration as well as practitioners from industry (especially data scientists), developers of expert databases, and software developers.

Machine Learning for Engineers

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    A Paperback by Marcus J. Neuer

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      Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
      Publication Date: Publication Date: 1/30/2024
      ISBN13: 9783662699942, 978-3662699942
      ISBN10: 366269994X

      Description

      Book Synopsis
      Machine learning and artificial intelligence are ubiquitous terms for improving technical processes. However, practical implementation in real-world problems is often difficult and complex. This textbook explains learning methods based on analytical concepts in conjunction with complete programming examples in Python, always referring to real technical application scenarios. It demonstrates the use of physics-informed learning strategies, the incorporation of uncertainty into modeling, and the development of explainable, trustworthy artificial intelligence with the help of specialized databases. Therefore, this textbook is aimed at students of engineering, natural science, medicine, and business administration as well as practitioners from industry (especially data scientists), developers of expert databases, and software developers.

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