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Beschreibung
Focusing on the fundamentals of machine learning, this book covers broad areas of data-driven modeling, ranging from simple regression to advanced machine learning and optimization methods for applications in materials modeling and discovery. The book explains complex mathematical concepts in a lucid manner to ensure that readers from different materials domains are able to use these techniques successfully. A unique feature of this book is its hands-on aspect—each method presented herein is accompanied by a code that implements the method in open-source platforms such as Python. This book is thus aimed at graduate students, researchers, and engineers to enable the use of data-driven methods for understanding and accelerating the discovery of novel materials.
Numerical Recipes and Practical Applications
Numerical Recipes and Practical Applications
Details
| Verlag | Springer International Publishing |
| Ersterscheinung | 07. Mai 2024 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 678 Gramm |
| Format | Hardcover |
| ISBN-13 | 9783031446214 |
| Seiten | 279 |
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