Seller: Antártica, Madrid, M, Spain
Rústica. Condition: New. Dust Jacket Condition: Nuevo. 1. 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. LIBRO.
Condition: New. 2024th edition NO-PA16APR2015-KAP.
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Machine Learning for Materials Discovery | Numerical Recipes and Practical Applications | N. M. Anoop Krishnan (u. a.) | Taschenbuch | Machine Intelligence for Materials Science | xx | Englisch | 2025 | Springer | EAN 9783031446245 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Seller: Brook Bookstore On Demand, Napoli, NA, Italy
Condition: new. Questo è un articolo print on demand.
Seller: Brook Bookstore On Demand, Napoli, NA, Italy
Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer International Publishing, Springer Nature Switzerland Mai 2024, 2024
ISBN 10: 3031446216 ISBN 13: 9783031446214
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 304 pp. Englisch.
Language: English
Published by Springer Verlag GmbH, 2025
ISBN 10: 3031446240 ISBN 13: 9783031446245
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
Language: English
Published by Springer International Publishing, 2024
ISBN 10: 3031446216 ISBN 13: 9783031446214
Seller: moluna, Greven, Germany
Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses various machine learning algorithms to address open problems in glass scienceProvides hands-on programming recipes by giving relevant codes for each sectionIntroduces machine learning for material informatics accessible to readers.
Language: English
Published by Springer, Springer Mai 2025, 2025
ISBN 10: 3031446240 ISBN 13: 9783031446245
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 304 pp. Englisch.
Condition: New. Print on Demand.
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND.
Seller: preigu, Osnabrück, Germany
Buch. Condition: Neu. Machine Learning for Materials Discovery | Numerical Recipes and Practical Applications | N. M. Anoop Krishnan (u. a.) | Buch | Machine Intelligence for Materials Science | xx | Englisch | 2024 | Springer | EAN 9783031446214 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Language: English
Published by Springer, Springer Mai 2025, 2025
ISBN 10: 3031446240 ISBN 13: 9783031446245
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 304 pp. Englisch.
Language: English
Published by Springer, Springer Mai 2024, 2024
ISBN 10: 3031446216 ISBN 13: 9783031446214
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 304 pp. Englisch.