Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Da: Majestic Books, Hounslow, Regno Unito
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Da: California Books, Miami, FL, U.S.A.
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 60,29
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 66,08
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Chiron Media, Wallingford, Regno Unito
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 72,34
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 77,95
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Da: Revaluation Books, Exeter, Regno Unito
EUR 84,94
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Aggiungi al carrelloPaperback. Condizione: Brand New. 260 pages. 9.25x6.10x0.71 inches. In Stock.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 84,21
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 92,98
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Condizione: New.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing, 2022
ISBN 10: 3030703908 ISBN 13: 9783030703905
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 58,84
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive problems now emerging. This text teaches state-of-the-art machine learning technologies to students and practicing engineers from the traditionally 'analog' disciplines-mechanical, aerospace, chemical, nuclear, and civil. Dr. McClarren examines these technologies from an engineering perspective and illustrates their specific value to engineers by presenting concrete examples based on physical systems. The book proceeds from basic learning models to deep neural networks, gradually increasing readers' ability to apply modern machine learning techniques to their current work and to prepare them for future, as yet unknown, problems. Rather than taking a black box approach, the author teaches a broad range of techniques while conveying the kinds of problems best addressed by each. Examples and case studies in controls, dynamics, heat transfer, and other engineering applications are implemented in Python and the libraries scikit-learn and tensorflow, demonstrating how readers can apply the most up-to-date methods to their own problems. The book equally benefits undergraduate engineering students who wish to acquire the skills required by future employers, and practicing engineers who wish to expand and update their problem-solving toolkit.
Da: preigu, Osnabrück, Germania
EUR 54,80
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Machine Learning for Engineers | Using data to solve problems for physical systems | Ryan G. McClarren | Taschenbuch | xiii | Englisch | 2022 | Springer | EAN 9783030703905 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: Revaluation Books, Exeter, Regno Unito
EUR 127,26
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Aggiungi al carrelloHardcover. Condizione: Brand New. 260 pages. 9.25x6.10x0.87 inches. In Stock.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing, 2021
ISBN 10: 3030703878 ISBN 13: 9783030703875
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 85,59
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive problems now emerging. This text teaches state-of-the-art machine learning technologies to students and practicing engineers from the traditionally 'analog' disciplines-mechanical, aerospace, chemical, nuclear, and civil. Dr. McClarren examines these technologies from an engineering perspective and illustrates their specific value to engineers by presenting concrete examples based on physical systems. The book proceeds from basic learning models to deep neural networks, gradually increasing readers' ability to apply modern machine learning techniques to their current work and to prepare them for future, as yet unknown, problems. Rather than taking a black box approach, the author teaches a broad range of techniques while conveying the kinds of problems best addressed by each. Examples and case studies in controls, dynamics, heat transfer, and other engineering applications are implemented in Python and the libraries scikit-learn and tensorflow, demonstrating how readers can apply the most up-to-date methods to their own problems. The book equally benefits undergraduate engineering students who wish to acquire the skills required by future employers, and practicing engineers who wish to expand and update their problem-solving toolkit.
Da: Majestic Books, Hounslow, Regno Unito
EUR 112,68
Quantità: 4 disponibili
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 112,98
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.