The term Numerical Linear Algebra refers to the use of matrices to solve computational science problems. In this chapter, we start by learning how to construct these objects effectively in Python. We make an emphasis on importing large sparse matrices from repositories online. We then proceed to reviewing basic manipulation and operations on them. The next step is a study of the different matrix functions implemented in SciPy. We continue on to exploring different factorizations for the solution of matrix equations, and for the computation of eigenvalues and their corresponding eigenvectors.
Mastering SciPy
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Mastering SciPy
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Overview of this book
Table of Contents (16 chapters)
Mastering SciPy
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Numerical Linear Algebra
Interpolation and Approximation
Differentiation and Integration
Nonlinear Equations and Optimization
Initial Value Problems for Ordinary Differential Equations
Computational Geometry
Descriptive Statistics
Inference and Data Analysis
Mathematical Imaging
Index
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