Learning Scipy for Numerical and Scientific Computing
Rojas, Sergio
Verkauft von GreatBookPrices, Columbia, MD, USA
AbeBooks-Verkäufer seit 6. April 2009
Neu - Softcover
Zustand: Neu
Anzahl: Mehr als 20 verfügbar
In den Warenkorb legenVerkauft von GreatBookPrices, Columbia, MD, USA
AbeBooks-Verkäufer seit 6. April 2009
Zustand: Neu
Anzahl: Mehr als 20 verfügbar
In den Warenkorb legenQuick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy
This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.
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.
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.
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