Applying Math with Python - Second Edition : Over 70 practical recipes for solving real-world computational math problems
Language: English
Published by Packt Publishing, 2022
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 68.57
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nach der Bestellung gedruckt Neuware - Printed after ordering - Discover easy-to-follow solutions and techniques to help you to implement applied mathematical concepts such as probability, calculus, and equations using Python's numeric and scientific librariesKey Features:Compute complex mathematical problems using programming logic with the help of step-by-step recipesLearn how to use Python libraries for computation, mathematical modeling, and statisticsDiscover simple yet effective techniques for solving mathematical equations and apply them in real-world statisticsBook Description:The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX.You'll start by refreshing your knowledge of several core mathematical fields and learn about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you progress, you'll gradually get to grips with more advanced topics of calculus, probability, and networks (graph theory). Once you've developed a solid base in these topics, you'll have the confidence to set out on math adventures with Python as you explore Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code.By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.What You Will Learn:Become familiar with basic Python packages, tools, and libraries for solving mathematical problemsExplore real-world applications of mathematics to reduce a problem in optimizationUnderstand the core concepts of applied mathematics and their application in computer scienceFind out how to choose the most suitable package, tool, or technique to solve a problemImplement basic mathematical plotting, change plot styles, and add labels to plots using MatplotlibGet to grips with probability theory with the Bayesian inference and Markov Chain Monte Carlo (MCMC) methodsWho this book is for:Whether you are a professional programmer or a student looking to solve mathematical problems computationally using Python, this is the book for you. Advanced mathematics proficiency is not a prerequisite, but basic knowledge of mathematics will help you to get the most out of this Python math book. Familiarity with the concepts of data structures in Python is assumed.…
Seller Inventory # 9781804618370
- Title
- Applying Math with Python - Second Edition : Over 70 practical recipes for solving real-world computational math problems
- Author
- Sam Morley
- Publisher
- Packt Publishing
- Publication year
- 2022
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1804618373
- ISBN 13
- 9781804618370
- Edition
- 2nd Edition
- Item weight
- 701 grams
- Dimensions
- 235x191x21 mm
Discover easy-to-follow solutions and techniques to help you to implement applied mathematical concepts such as probability, calculus, and equations using Python's numeric and scientific libraries
Key Features
- Compute complex mathematical problems using programming logic with the help of step-by-step recipes
- Learn how to utilize Python's libraries for computation, mathematical modeling, and statistics
- Discover simple yet effective techniques for solving mathematical equations and apply them in real-world statistics
Book Description
The updated edition of Applying Math with Python will help you tackle complex mathematical problems simply and efficiently. These core capabilities help programmers pave the way for building exciting applications in various domains, such as machine learning and data science, using knowledge in the computational mathematics domain.
The book teaches you how to solve problems faced in a wide variety of mathematical fields, including calculus, probability, statistics and data science, graph theory, optimization, and geometry. You'll start by developing core skills and learning about packages covered in Python’s scientific stack, including NumPy, SciPy, and Matplotlib. As you advance, you'll get to grips with more advanced topics of calculus, probability, and networks (graph theory). After you gain a solid understanding of these topics, you'll discover Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code.
By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.
What you will learn
- Get familiar with basic packages, tools, and libraries in Python for solving mathematical problems
- Explore various techniques that will help you to solve computational mathematical problems
- Understand the core concepts of applied mathematics and how you can apply them in computer science
- Discover how to choose the most suitable package, tool, or technique to solve a certain problem
- Implement basic mathematical plotting, change plot styles, and add labels to the plots using Matplotlib
- Get to grips with probability theory with the Bayesian inference and Markov Chain Monte Carlo (MCMC) methods
Who This Book Is For
This book is for professional programmers and students looking to solve mathematical problems computationally using Python. Advanced mathematics knowledge is not a requirement, but a basic knowledge of mathematics will help you to get the most out of this book. The book assumes familiarity with Python concepts of data structures.
Table of Contents
- An Introduction to Basic Packages, Functions, and Concepts
- Mathematical Plotting Using Matplotlib
- Calculus and differential equations
- Working with randomness
- Trees and networks
- Working with data and statistics
- Regression and forecasting
- Geometric problems
- Finding optimal solutions
- Improving your productivity
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"About the title" may belong to another edition of this title.
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