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Learning scientific programming with Python

Learn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial pack...

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Detalles Bibliográficos
Autor principal: Hill, Christian
Lenguaje:eng
Publicado: Cambridge University Press 2015
Materias:
Acceso en línea:https://dx.doi.org/10.1017/CBO9781139871754
http://cds.cern.ch/record/2126971
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author Hill, Christian
author_facet Hill, Christian
author_sort Hill, Christian
collection CERN
description Learn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targeted package for students requiring a solid foundation in Python programming.
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spelling cern-21269712021-04-21T19:49:27Zdoi:10.1017/CBO9781139871754http://cds.cern.ch/record/2126971engHill, ChristianLearning scientific programming with PythonComputing and ComputersLearn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targeted package for students requiring a solid foundation in Python programming.Cambridge University Pressoai:cds.cern.ch:21269712015
spellingShingle Computing and Computers
Hill, Christian
Learning scientific programming with Python
title Learning scientific programming with Python
title_full Learning scientific programming with Python
title_fullStr Learning scientific programming with Python
title_full_unstemmed Learning scientific programming with Python
title_short Learning scientific programming with Python
title_sort learning scientific programming with python
topic Computing and Computers
url https://dx.doi.org/10.1017/CBO9781139871754
http://cds.cern.ch/record/2126971
work_keys_str_mv AT hillchristian learningscientificprogrammingwithpython