Machine Learning for Materials Discovery Numerical Recipes and Practical Applications /
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 luci...
Gardado en:
| Main Authors: | , , |
|---|---|
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2024.
|
| Edición: | 1st ed. 2024. |
| Series: | Machine Intelligence for Materials Science,
|
| Subjects: | |
| Acceso en liña: | https://doi.org/10.1007/978-3-031-44622-1 |
| Tags: |
Engadir etiqueta
Sen Etiquetas, Sexa o primeiro en etiquetar este rexistro!
|
| Summary: | 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. |
|---|---|
| Descrición Física: | 1 online resource (XX, 279 p. 110 illus.). 95 illus. in color. |
| ISBN: | 9783031446221 |
| ISSN: | 2948-1821 |
| DOI: | 10.1007/978-3-031-44622-1 |