Algorithms with JULIA: Optimization, Machine Learning, and Differential Equations Using the JULIA Language - Tapa dura
Sinopsis
This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (artificial neural networks and Bayesian estimation).
JULIA is a relatively new programming language which has been developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system.
Aimed at students ofapplied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming.
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Acerca del autor
Clemens Heitzinger is Associate Professor at the TU Vienna.
De la contraportada
This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (artificial neural networks and Bayesian estimation).
JULIA is a relatively new programming language which has been developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system.
Aimed at students of applied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming.
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Algorithms with JULIA (Hardcover)
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Springer International Publishing AG, Cham, 2022
ISBN 10: 3031165594
ISBN 13: 9783031165597
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Hardcover. Condición: new. Hardcover. This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (artificial neural networks and Bayesian estimation).JULIA is a relatively new programming language which has been developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system. Aimed at students ofapplied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming. This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783031165597
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Algorithms with JULIA: Optimization, Machine Learning, and Differential Equations Using the JULIA Language
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Hardcover. Condición: Brand New. 460 pages. 9.25x6.10x1.14 inches. In Stock. Nº de ref. del artículo: __3031165594
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Algorithms with JULIA
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Springer International Publishing AG, 2022
ISBN 10: 3031165594
ISBN 13: 9783031165597
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Algorithms with JULIA
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Springer International Publishing, Springer Nature Switzerland Dez 2022, 2022
ISBN 10: 3031165594
ISBN 13: 9783031165597
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (artificial neural networks and Bayesian estimation).JULIA is a relatively new programming language which has been developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system. Aimed at students ofapplied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming. 464 pp. Englisch. Nº de ref. del artículo: 9783031165597
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Algorithms with JULIA
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Springer International Publishing, 2022
ISBN 10: 3031165594
ISBN 13: 9783031165597
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Librería: moluna, Greven, Alemania
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Written at an introductory levelUsing JULIA on a non-trivial application levelIncludes discussion of JULIA as an open-source alternative for MATLABClemens Heitzinger is Associate Professor at the TU Vienna. Nº de ref. del artículo: 673508247
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Algorithms with JULIA
Publicado por
Springer International Publishing, Springer Nature Switzerland Dez 2022, 2022
ISBN 10: 3031165594
ISBN 13: 9783031165597
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Buch. Condición: Neu. Neuware -This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (artificial neural networks and Bayesian estimation).JULIA is a relatively new programming language which has been developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system.Aimed at students ofapplied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 464 pp. Englisch. Nº de ref. del artículo: 9783031165597
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Algorithms with JULIA | Optimization, Machine Learning, and Differential Equations Using the JULIA Language
Publicado por
Springer International Publishing, 2022
ISBN 10: 3031165594
ISBN 13: 9783031165597
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Librería: preigu, Osnabrück, Alemania
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Buch. Condición: Neu. Algorithms with JULIA | Optimization, Machine Learning, and Differential Equations Using the JULIA Language | Clemens Heitzinger | Buch | XXI | Englisch | 2022 | Springer International Publishing | EAN 9783031165597 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 122979683
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Algorithms with JULIA : Optimization, Machine Learning, and Differential Equations Using the JULIA Language
Publicado por
Springer International Publishing, Springer Nature Switzerland, 2022
ISBN 10: 3031165594
ISBN 13: 9783031165597
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (artificial neural networks and Bayesian estimation).JULIA is a relatively new programming language which has been developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system. Aimed at students ofapplied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming. Nº de ref. del artículo: 9783031165597
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Algorithms with JULIA (Hardcover)
Publicado por
Springer International Publishing AG, Cham, 2022
ISBN 10: 3031165594
ISBN 13: 9783031165597
Nuevo
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Librería: AussieBookSeller, Truganina, VIC, Australia
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Hardcover. Condición: new. Hardcover. This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (artificial neural networks and Bayesian estimation).JULIA is a relatively new programming language which has been developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system. Aimed at students ofapplied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming. This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9783031165597
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