9783031662522 - statistical machine learning for engineering with applications: 227 (15 risultati)
Lingua: Inglese
Editore: Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: Books From California, Simi Valley, CA, U.S.A.Books From California
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paperback. Condizione: Very Good. Cover and edges may have some wear.
Lingua: Inglese
Editore: Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Lingua: Inglese
Editore: Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. 2024th edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New.
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Editore: Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Condizione: New.
Lingua: Inglese
Editore: Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Condizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Editore: Springer International Publishing AG, Cham 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Paperback. Condizione: new. Paperback. This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiments, and related methods. For ease of reading, technical details are avoided…as far as possible, and there is a particular emphasis on applicability, interpretation, reliability and limitations of the data-analytic methods in practice. To cover the common availability and types of data in engineering, training sets consisting of independent as well as time series data are considered. To cope with the scarceness of data in industrial problems, augmentation of training sets by additional artificial data, generated from physical models, as well as the combination of machine learning and expert knowledge of engineers are discussed.The methodological exposition is accompanied by several detailed case studies based on industrial projects covering a broad range of engineering applications from vehicle manufacturing, process engineering and design of materials to optimization of production processes based on image analysis.The focus is on fundamental ideas, applicability and the pitfalls of machine learning in industry and science, where data are often scarce. Requiring only very basic background in statistics, the book is ideal for self-study or short courses for engineering and science students. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Statistical Machine Learning for Engineering with Applications | Jürgen Franke (u. a.) | Taschenbuch | Lecture Notes in Statistics | viii | Englisch | 2024 | Springer | EAN 9783031662522 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartm…ann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer Nature 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 400 pages. 9.25x6.10x9.21 inches. In Stock.
Lingua: Inglese
Editore: Springer, Palgrave Macmillan 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiments, and related methods. For eas…e of reading, technical details are avoided as far as possible, and there is a particular emphasis on applicability, interpretation, reliability and limitations of the data-analytic methods in practice. To cover the common availability and types of data in engineering, training sets consisting of independent as well as time series data are considered. To cope with the scarceness of data in industrial problems, augmentation of training sets by additional artificial data, generated from physical models, as well as the combination of machine learning and expert knowledge of engineers are discussed.The methodological exposition is accompanied by several detailed case studies based on industrial projects covering a broad range of engineering applications from vehicle manufacturing, process engineering and design of materials to optimization of production processes based on image analysis.The focus is on fundamental ideas, applicability and the pitfalls of machine learning in industry and science, where data are often scarce. Requiring only very basic background in statistics, the book is ideal for self-study or short courses for engineering and science students.
Lingua: Inglese
Editore: Springer, Palgrave Macmillan Okt 2024 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiments, and related…methods. For ease of reading, technical details are avoided as far as possible, and there is a particular emphasis on applicability, interpretation, reliability and limitations of the data-analytic methods in practice. To cover the common availability and types of data in engineering, training sets consisting of independent as well as time series data are considered. To cope with the scarceness of data in industrial problems, augmentation of training sets by additional artificial data, generated from physical models, as well as the combination of machine learning and expert knowledge of engineers are discussed.The methodological exposition is accompanied by several detailed case studies based on industrial projects covering a broad range of engineering applications from vehicle manufacturing, process engineering and design of materials to optimization of production processes based on image analysis.The focus is on fundamental ideas, applicability and the pitfalls of machine learning in industry and science, where data are often scarce. Requiring only very basic background in statistics, the book is ideal for self-study or short courses for engineering and science students. 400 pp. Englisch.
Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Switzerland|Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: moluna, Greven, , Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiment…s, and related methods. For ease of re.
Lingua: Inglese
Editore: Springer 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
- Brossura
- Print on Demand
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer, Springer Okt 2024 2024
Serie: Lecture Notes in Statistics, Libro 72 di 72. Libro 72 di 72 - Lecture Notes in Statistics
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiments, and related meth…ods. For ease of reading, technical details are avoided as far as possible, and there is a particular emphasis on applicability, interpretation, reliability and limitations of the data-analytic methods in practice. To cover the common availability and types of data in engineering, training sets consisting of independent as well as time series data are considered. To cope with the scarceness of data in industrial problems, augmentation of training sets by additional artificial data, generated from physical models, as well as the combination of machine learning and expert knowledge of engineers are discussed.The methodological exposition is accompanied by several detailed case studies based on industrial projects covering a broad range of engineering applications from vehicle manufacturing, process engineering and design of materials to optimization of production processes based on image analysis.The focus is on fundamental ideas, applicability and the pitfalls of machine learning in industry and science, where data are often scarce. Requiring only very basic background in statistics, the book is ideal for self-study or short courses for engineering and science students.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 400 pp. Englisch.
