Name: Machine Learning for Engineers: Introduction to Physics-Informed, Explainable Learning Methods for ai in Engineering Applications (en Inglés)
SKU: 64156134
Price: 59.53 USD
Availability: InStock
Author: Marcus J. Neuer

portada Machine Learning for Engineers: Introduction to Physics-Informed, Explainable Learning Methods for ai in Engineering Applications (en Inglés)

Machine Learning for Engineers: Introduction to Physics-Informed, Explainable Learning Methods for ai in Engineering Applications (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Marcus J. Neuer

Idioma

Inglés

N° páginas

241

Encuadernación

Tapa Blanda

ISBN13

9783662699942

N° edición

2024th

Machine Learning for Engineers: Introduction to Physics-Informed, Explainable Learning Methods for ai in Engineering Applications (en Inglés)

Marcus J. Neuer (Autor) · Springer · Tapa Blanda

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Reseña del libro "Machine Learning for Engineers: Introduction to Physics-Informed, Explainable Learning Methods for ai in Engineering Applications (en Inglés)"

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.