Statistical machine learning engineering (17 resultados)
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Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Editorial: Springer, 2024
Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Paperback. Condición: 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 a…s 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.
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Taschenbuch. Condición: Neu. Neuware.
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Editorial: Springer, 2024
Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Taschenbuch. Condición: 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]hartma…nn[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Editorial: Springer Nature, 2024
Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Paperback. Condición: Brand New. 400 pages. 9.25x6.10x9.21 inches. In Stock.
Idioma: Inglés
Editorial: Springer, Palgrave Macmillan, 2024
Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: 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 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.
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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Condición: New. Print on Demand.
Idioma: Inglés
Editorial: Springer, Palgrave Macmillan Okt 2024, 2024
Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: 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 m…ethods. 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.
Idioma: Inglés
Editorial: Springer, 2024
Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condición: new. Questo è un articolo print on demand.
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Editorial: Springer, Berlin|Springer Nature Switzerland|Springer, 2024
Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Librería: moluna, Greven, Alemaniamoluna
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Condición: 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 experiments…, and related methods. For ease of re.
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Editorial: Springer, Springer Okt 2024, 2024
Serie: Lecture Notes in Statistics, Libro 72 de 72. Libro 72 de 72 - Lecture Notes in Statistics
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: 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 metho…ds. 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.
