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scientific simulations and computer graphics and including an overview of available (scientific) libraries. Uses the C programming language, and;
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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The;
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so solve typical scientific and engineering problems. It is a learning-by-doing book, with many examples and exercises, and lays a foundation;
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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The;
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A Scientific Approach to Problem-Solving with C++ Programming teaches the basic concepts needed to master C++, illustrating every building;
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The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike widely;
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The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike widely;
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of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such;
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look at how a computer really works. This book examines and explains a variety of scientific programming models (programming models relevant to;
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Designed for undergraduates, An Introduction to High-Performance Scientific Computing assumes a basic knowledge of numerical computation;
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of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis;
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Parallel Programming with Co-Arrays describes the basic techniques used to design parallel algorithms for high-performance, scientific;
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Taking an interdisciplinary approach, this new book provides a modern introduction to scientific computing, exploring numerical methods;
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Taking an interdisciplinary approach, this new book provides a modern introduction to scientific computing, exploring numerical methods;
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attention has been paid to XML in mainstream computational science and engineering. Correcting this imbalance, XML in Scientific Computing;
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attention has been paid to XML in mainstream computational science and engineering. Correcting this imbalance, XML in Scientific Computing;
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Linear programming (LP), as a specific case of mathematical programming, has been widely encountered in a broad class of scientific;
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Learn How to Program Stochastic Models Highly recommended, the best-selling first edition of Introduction to Scientific Programming and;
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solve scientific problems, especially the numerical ones. The main audience of this book is mathematics, biology, physics and engineering;
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, physical system modelling, scientific graphics, software engineering and performance issues. Compact, transparent code in all three programming;
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solve science and engineering problems.Many examples are included from a number of different scientific and engineering areas, as;
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variables, message passing, and Linda -- and shows how each can be used to solve various scientific and numerical problems. Examples, coded;
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Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics;
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Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics;
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Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics;
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