Quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy
About This Book
Who This Book Is For
This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.
What You Will Learn
In Detail
SciPy is an open source Python library used to perform scientific computing. The SciPy (Scientific Python) package extends the functionality of NumPy with a substantial collection of useful algorithms.
The book starts with a brief description of the SciPy libraries, followed by a chapter that is a fun and fast-paced primer on array creation, manipulation, and problem-solving. You will also learn how to use SciPy in linear algebra, which includes topics such as computation of eigenvalues and eigenvectors. Furthermore, the book is based on interesting subjects such as definition and manipulation of functions, computation of derivatives, integration, interpolation, and regression. You will also learn how to use SciPy in signal processing and how applications of SciPy can be used to collect, organize, analyze, and interpret data.
By the end of the book, you will have fast, accurate, and easy-to-code solutions for numerical and scientific computing applications.
"synopsis" may belong to another edition of this title.
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.
"About this title" may belong to another edition of this title.
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