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9783031165597: Algorithms with JULIA: Optimization, Machine Learning, and Differential Equations Using the JULIA Language

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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Clemens Heitzinger is Associate Professor at the TU Vienna.

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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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9783031165627: Algorithms with JULIA: Optimization, Machine Learning, and Differential Equations Using the JULIA Language

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ISBN 10:  3031165624 ISBN 13:  9783031165627
Editorial: Springer-Verlag GmbH, 2023
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Heitzinger, Clemens (Author)
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ISBN 10: 3031165594 ISBN 13: 9783031165597
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Clemens Heitzinger
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ISBN 10: 3031165594 ISBN 13: 9783031165597
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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&nbspAssociate Professor at the&nbspTU Vienna. Nº de ref. del artículo: 673508247

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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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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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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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