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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

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781804618370
Length 376 pages
Edition 2nd Edition
Languages
Concepts
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Author (1):
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Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
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Table of Contents (13) Chapters Close

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 12. Other Books You May Enjoy

Improving Your Productivity

In this chapter, we will look at several topics that don’t fit within the categories that we discussed in the previous chapters of this book. Most of these topics are concerned with different ways to facilitate computing and otherwise optimize the execution of our code. Others are concerned with working with specific kinds of data or file formats.

The aim of this chapter is to provide you with some tools that, while not strictly mathematical in nature, often appear in mathematical problems. These include topics such as distributed computing and optimization – both help you to solve problems more quickly, validate data and calculations, load and store data from file formats commonly used in scientific computation, and incorporate other topics that will generally help you be more productive with your code.

In the first two recipes, we will cover packages that help keep track of units and uncertainties in calculations. These are very important...

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