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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

A good, comprehensive reference for probability and random processes is the following book:

Grimmett, G. and Stirzaker, D. (2009). Probability and random processes. 3rd ed. Oxford: Oxford Univ. Press.

An easy introduction to Bayes’ theorem and Bayesian statistics is the following:

Kurt, W. (2019). Bayesian statistics the fun way. San Francisco, CA: No Starch Press, Inc.

The rest of the chapter is locked

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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.

See other products by Morley

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