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Published by Springer Nature Singapore, 2024
ISBN 10: 9819903955 ISBN 13: 9789819903955
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material's electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.
Published by Springer Verlag, Singapore, Singapore, 2023
ISBN 10: 9819903920 ISBN 13: 9789819903924
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Hardcover. Condition: new. Hardcover. This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the materials electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods. This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Springer Nature Singapore, 2023
ISBN 10: 9819903920 ISBN 13: 9789819903924
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Published by Springer Nature Singapore Mai 2023, 2023
ISBN 10: 9819903920 ISBN 13: 9789819903924
Language: English
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Add to basketBuch. Condition: Neu. Neuware -This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material¿s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 312 pp. Englisch.
Published by Springer Nature Singapore, 2023
ISBN 10: 9819903920 ISBN 13: 9789819903924
Language: English
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material's electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.
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Add to basketHardcover. Condition: Brand New. 311 pages. 9.25x6.10x0.71 inches. In Stock.
Published by Springer Nature Singapore Mai 2024, 2024
ISBN 10: 9819903955 ISBN 13: 9789819903955
Language: English
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 312 pp. Englisch.
Published by Springer, Berlin|Springer Nature Singapore|Springer, 2024
ISBN 10: 9819903955 ISBN 13: 9789819903955
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct.
Published by Springer Nature Singapore Mai 2024, 2024
ISBN 10: 9819903955 ISBN 13: 9789819903955
Language: English
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material¿s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 312 pp. Englisch.
Published by Springer, Berlin|Springer Nature Singapore|Springer, 2023
ISBN 10: 9819903920 ISBN 13: 9789819903924
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct.
Published by Springer Nature Singapore Mai 2023, 2023
ISBN 10: 9819903920 ISBN 13: 9789819903924
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Add to basketBuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material's electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods. 312 pp. Englisch.