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Introduction to the tools of scienti...

Smith, Einar.

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Introduction to the tools of scientific computing

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to the tools of scientific computing/ by Einar Smith.
作者:	Smith, Einar.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xiii, 428 p. :ill., digital ;24 cm.
內容註:	Introduction -- Part I, Background -- Part II, Core Languages -- Part III, Commercial Computing Environments -- Part IV, Distributed Computing -- Part V, Specialized Programming Environments -- References -- Index.
Contained By:	Springer Nature eBook
標題:	Computer science - Mathematics. -
電子資源:	https://doi.org/10.1007/978-3-031-16972-4
ISBN:	9783031169724

Introduction to the tools of scientific computing
Smith, Einar.

Introduction to the tools of scientific computing[electronic resource] /by Einar Smith. - Second edition. - Cham :Springer International Publishing :2022. - xiii, 428 p. :ill., digital ;24 cm. - Texts in computational science and engineering,v. 252197-179X ;. - Texts in computational science and engineering ;v. 25..

Introduction -- Part I, Background -- Part II, Core Languages -- Part III, Commercial Computing Environments -- Part IV, Distributed Computing -- Part V, Specialized Programming Environments -- References -- Index.

The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike standard approaches, it does not focus on any specific language, but aims to explain the underlying ideas. Typically, new concepts are first introduced in the particularly user-friendly Python language and then transferred and extended in various programming environments from C/C++, Julia and MATLAB to Maple and Mathematica. This includes various approaches to distributed computing. By examining and comparing different languages, the book is also helpful for mathematicians and practitioners in deciding which programming language to use for which purposes. At a more advanced level, special tools for the automated solution of partial differential equations using the finite element method are discussed. On a more experimental level, the basic methods of scientific machine learning in artificial neural networks are explained and illustrated.

ISBN: 9783031169724

Standard No.: 10.1007/978-3-031-16972-4doiSubjects--Topical Terms:

532725
Computer science
--Mathematics.

LC Class. No.: QA76.9.M35 / S55 2022

Dewey Class. No.: 004.0151

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