Introduction to the Tools of Scientific Computing - Smith, Einar
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The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike widely used standard approaches, it does not focus on any particular language but aims to explain the key underlying concepts.
In general, new concepts are first introduced in the particularly user-friendly Python language and then transferred and expanded in various scientific programming environments from C / C ++, Julia and MATLAB to Maple. This includes different approaches to distributed computing.
The fact that different languages are studied and…mehr

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Produktbeschreibung
The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike widely used standard approaches, it does not focus on any particular language but aims to explain the key underlying concepts.

In general, new concepts are first introduced in the particularly user-friendly Python language and then transferred and expanded in various scientific programming environments from C / C ++, Julia and MATLAB to Maple. This includes different approaches to distributed computing.

The fact that different languages are studied and compared also makes the book useful for mathematicians and practitioners trying to decide which programming language to use for which purposes.

Autorenporträt
Einar Smith holds academic degrees in Mathematics from the Unversity of Bonn, in Economics from the University of Oslo, and in Computer Science from the University of Hamburg.  He has published a textbook on Mathematical Computability Theory, and a biography of the German computer scientist C.A. Petri. Both books have been published by Springer. In recent years he has mainly been concerned with the teaching of numerical methods at the University of Bonn, with an emphasis on computer programming.
Rezensionen
"This book covers a lot of ground, and overall it does so very well. ... On nearly every page, the reader can find numerous code snippets ... that are explained in great detail. ... I can warmly recommend it to my colleagues and STEM students as a welcome resource to help them with this decision tree." (Andreas Mang, SIAM Review, Vol. 64 (2), June, 2022)