Machine Learning in 2D Materials Science (PDF)
(Sprache: Englisch)
This book provides broad coverage of data science and ML fundamentals to materials science researchers so that they can confidently leverage these techniques in their research projects.
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This book provides broad coverage of data science and ML fundamentals to materials science researchers so that they can confidently leverage these techniques in their research projects.
Autoren-Porträt
Parvathi Chundi, PhD is Professor of Computer Science, University of Nebraska-Omaha. Prior to Omaha, Dr. Chundi was with Agilent Technologies and HP Labs, both in Palo Alto, CA.Venkataramana Gadhamshetty, PhD, PE is Professor of Environmental Engineering in Department of Civil and Environmental Engineering, South Dakota School of Mines and Technology. He is a cofounder of 2D materials for Biofilm Science Engineering and Technology (2DBEST) center and 2D materials laboratory (2DML) at SDSM&T.
Bharat K. Jasthi, PhD is Associate Professor, Department of Materials and Metallurgical Engineering, South Dakota School of Mines and Technology. Dr. Jasthi has research expertise in the areas of microstructural modification, structure property correlation, new alloy development, powder metallurgy, additive manufacturing, and development of engineered surface thin films and coatings for a wide range of applications.
Carol Lushbough, MA is an Emeritus Professor of Computer Science, University of South Dakota.
Bibliographische Angaben
- 2023, 1. Auflage, 248 Seiten, Englisch
- Herausgegeben: Parvathi Chundi, Venkataramana Gadhamshetty, Bharat K. Jasthi, Carol Lushbough
- Verlag: Taylor & Francis
- ISBN-10: 1000987434
- ISBN-13: 9781000987430
- Erscheinungsdatum: 13.11.2023
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Größe: 27 MB
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Sprache:
Englisch
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