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Applying Math with Python

You're reading from Applying Math with Python Over 70 practical recipes for solving real-world computational math problems

Product type Paperback

Published in Dec 2022

Publisher Packt

ISBN-13 9781804618370

Length 376 pages

Edition 2nd Edition

Languages

Python

Tools

Matplotlib

Concepts

Statistics

Author (1):

Sam Morley

View More author details

Table of Contents (13) Chapters

Preface

1. Chapter 1: An Introduction to Basic Packages, Functions, and Concepts

2. Chapter 2: Mathematical Plotting with Matplotlib FREE CHAPTER

3. Chapter 3: Calculus and Differential Equations

4. Chapter 4: Working with Randomness and Probability

5. Chapter 5: Working with Trees and Networks

6. Chapter 6: Working with Data and Statistics

7. Chapter 7: Using Regression and Forecasting

8. Chapter 8: Geometric Problems

9. Chapter 9: Finding Optimal Solutions

10. Chapter 10: Improving Your Productivity

11. Index

Why subscribe?

12. Other Books You May Enjoy

Further reading

There are many mathematical textbooks describing the basic properties of matrices and linear algebra, which is the study of vectors and matrices. The following are good introductory texts for linear algebra:

Strang, G. (2016). Introduction to Linear Algebra. Wellesley, MA: Wellesley-Cambridge Press, Fifth Edition.
Blyth, T. and Robertson, E. (2013). Basic Linear Algebra. London: Springer London, Limited.

NumPy and SciPy are part of the Python mathematical and scientific computing ecosystem and have extensive documentation that can be accessed from the official website, https://scipy.org. We will see several other packages from this ecosystem throughout this book.

More information about the BLAS and LAPACK libraries that NumPy and SciPy use behind the scenes can be found at the following links:

BLAS: https://www.netlib.org/blas/
LAPACK: https://www.netlib.org/lapack/

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Authors (1)

Morley

Morley

Sam Morley is an experienced lecturer in mathematics and a researcher in pure mathematics. He is currently a research software engineer at the University of Oxford working on the DataSig project. He was previously a lecturer in mathematics at the University of East Anglia and Nottingham Trent University. His research interests lie in functional analysis, especially Banach algebras. Sam has a firm commitment to providing high-quality, inclusive, and enjoyable teaching, with the aim of inspiring his students and spreading his enthusiasm for mathematics.

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