Machine Learning for the Physical Sciences (PDF)
Fundamentals and Prototyping with Julia
(Sprache: Englisch)
This textbook bridges this gap, providing an introduction to the mathematical foundations for the main algorithms used in machine learning for those from the physical sciences, without a formal background in computer science.
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This textbook bridges this gap, providing an introduction to the mathematical foundations for the main algorithms used in machine learning for those from the physical sciences, without a formal background in computer science.
Autoren-Porträt von Carlo Requião Da Cunha
Carlo R. da Cunha is currently an assistant professor at the School of Informatics, Computing, and Cyber Systems at Northern Arizona University. He holds a Ph.D. degree in electrical engineering from Arizona State University. Throughout his career, Dr. da Cunha has held various academic positions and research affiliations in institutions such as McGill University, Chiba University, and the Technical University of Vienna. His research focuses on computational science, where he applies machine learning techniques to the design of innovative electronic devices and systems.
Bibliographische Angaben
- Autor: Carlo Requião Da Cunha
- 2023, 1. Auflage, 288 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1003821146
- ISBN-13: 9781003821144
- Erscheinungsdatum: 11.12.2023
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Dateiformat: PDF
- Grösse: 20 MB
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Sprache:
Englisch
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