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- Get to know the benefits of using the combination of Python, NumPy, SciPy, and matplotlib as a programming environment for scientific purposes
- Create and manipulate an object array used by SciPy
- Use SciPy with large matrices to compute eigenvalues and eigenvectors
- Focus on construction, acquisition, quality improvement, compression, and feature extraction of signals
- Make use of SciPy to collect, organize, analyze, and interpret data, with examples taken from statistics and clustering
- Acquire the skill of constructing a triangulation of points, convex hulls, Voronoi diagrams, and many similar applications
- Find out ways that SciPy can be used with other languages such as C/C++, Fortran, and MATLAB/Octave

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Publication date :
Feb 26, 2015

Length
188 pages

Edition :
1st Edition

Language :
English

ISBN-13 :
9781783987702

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Learning SciPy for Numerical and Scientific Computing Second Edition

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Preface

1. Introduction to SciPy

2. Working with the NumPy Array As a First Step to SciPy

3. SciPy for Linear Algebra

4. SciPy for Numerical Analysis

5. SciPy for Signal Processing

6. SciPy for Data Mining

7. SciPy for Computational Geometry

8. Interaction with Other Languages

Index

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