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Total Size:
34.0 MB
Info Hash:
DA965F1835EE2CA2DEE796F881B58A3EA17E8B67
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Added:
May 26, 2025, 11:59 a.m.
Stats:
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(Last updated: May 26, 2025, 12:01 p.m.)
| File | Size |
|---|---|
| Knight V. Python for Mathematics 2025.pdf | 16.5 MB |
| Guillod J. Python Programming for Mathematics 2024.pdf | 17.5 MB |
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34.0 MB
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2025-05-26
| Uploaded by andryold1 | Size 34.0 MB | Health [ 127 /43 ] | Added 2025-05-26 |
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130.2 MB
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2023-10-10
| Uploaded by IGGGAMES | Size 130.2 MB | Health [ 45 /16 ] | Added 2023-10-10 |
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638.3 MB
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2023-10-12
| Uploaded by indexFroggy | Size 638.3 MB | Health [ 21 /3 ] | Added 2023-10-12 |
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159.0 MB
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2023-10-21
| Uploaded by IGGGAMESCOM | Size 159.0 MB | Health [ 0 /1 ] | Added 2023-10-21 |
NOTE
SOURCE: Knight V. Python for Mathematics 2025
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COVER
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MEDIAINFO
Textbook in PDF format Python for Mathematics introduces readers to effective methods for doing mathematics using the Python programming language. Most programming texts introduce readers to the building blocks of programming and build up to using more sophisticated tools for a specific purpose, like doing particular mathematical tasks. This is akin to teaching someone how to forge metal so as to make a nail, and then slowly working up to using sophisticated power tools so as to actually build something. This book does things in a different way, by first getting readers to begin using and understanding the tools that are going to be helpful to them as mathematicians, and only then moving onto the granular details. In this way, the practical application of the tools can aid in the understanding of the theory. This book aims to be a user guide for how the Python programming language can be used to reduce mechanical calculation which leaves more space to do real mathematics. Whilst no book should ever try to stop a mathematician from picking up a pen and pencil and thinking about a problem, this one does aim to show how modern mathematicians can replace, some of, the use of their pen with openly available Python tools. For example, in Chapter 3, how to solve an equation by essentially just writing it down is covered. In Chapter 7 probabilities of specific events are simulated. In the second part of this book, a more traditional approach of programming with Python is used to show how to build tools. Not only does this cover commonly taught programming techniques but also goes into principles of software development used in industry. For example, Chapter 16 covers a modern way of writing documentation for software and Chapter 17 covers how to write code that tests software. This book is for you, whether you are a seasoned professional mathematician who would like to know some of the best practices for using Python or perhaps more typically, if you are a first year university student with an understanding of the mathematical topics covered. I hope you enjoy it. Features · Complete with engaging, practical exercises · Many useful and detailed coding examples · Suitable for undergraduates in mathematics, and other quantitative sciences · Empowers readers to design and create their own Python tools. Preface Section I Overview Introduction Section II Tools for Mathematics Using Notebooks Algebra Calculus Matrices Combinatorics Probability Sequences Statistics Differential Equations Section III Building Tools Variables, Conditionals and Loops Functions and Data Structures Object-Oriented Programming Using a Command Line and an Editor Modularisation Documentation Testing Section IV About This Book How This Book Is Written
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