Learning SciPy for Numerical and Scientific Computing - Second Edition
Sergio J.
Rojas G.
Sergio J.
Rojas G.
is currently a full professor of physics at Universidad Simon Bolivar, Venezuela.
Regarding his formal studies, in 1991, he earned a BS in physics with his thesis on numerical relativity from the Universidad de Oriente, Estado Sucre, Venezuela, and then, in 1998, he earned a PhD in physics from the Department of Physics at City College of the City University of New York, where he worked on the applications of fluid dynamics in the flow of fluids in porous media, gaining and developing since then a vast experience in programming as an aid to scientific research via Fortran77/90 and C/C++.
In 2001, he also earned a master's degree in computational finance from the Oregon Graduate Institute of Science and Technology.
Sergio's teaching activities involve lecturing undergraduate and graduate physics courses at his home university, Universidad Simon Bolivar, Venezuela, including a course on Monte Carlo methods and another on computational finance.
His research interests include physics education research, fluid flow in porous media, and the application of the theory of complex systems and statistical mechanics in financial engineering.
More recently, Sergio has been involved in machine learning and its applications in science and engineering via the Python programming language.
- First published
- Feb 26, 2015
- Publishers
- Packt Publishing
This book provide a very good starting point to start using scipy for scientific computing. The book start with a basic python training and then continues with scipy proper.
This book starts by providing a good detailed introduction into the use of Numpy arrays. It continues with a very limited introduction into the many powerful SciPy modules.
A well written manual for learning to use Scipy. On the other hand some very good doc can be found on the internet: eg.
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