Applying Math with Python - Second Edition: Over 70 practical recipes for solving real-world computational math problems

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 use Python 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 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 problems
• Explore real-world applications of mathematics to reduce a problem in optimization
• Understand the core concepts of applied mathematics and their application in computer science
• Find out how to choose the most suitable package, tool, or technique to solve a problem
• Implement basic mathematical plotting, change plot styles, and add labels to 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:

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.

發現易於遵循的解決方案和技巧，以幫助您使用Python的數值和科學庫實施應用數學概念，如概率、微積分和方程式。

主要特點：

- 使用逐步的配方，使用編程邏輯計算複雜的數學問題
- 學習如何使用Python庫進行計算、數學建模和統計
- 發現簡單而有效的技巧來解決數學方程式，並在實際統計中應用它們

書籍描述：

《應用數學與Python》的更新版將幫助您以簡單高效的方式解決各種數學領域的複雜問題。舊的配方已經為新的庫進行了修訂，並添加了一些配方來演示新的工具，如JAX。

您將首先回顧幾個核心數學領域的知識，並了解Python科學堆棧中涵蓋的包，包括NumPy、SciPy和Matplotlib。隨著進展，您將逐漸掌握更高級的微積分、概率和網絡（圖論）等主題。一旦您在這些主題上建立了堅實的基礎，您將有信心以Python為基礎進行數據科學和統計、預測、幾何和優化等領域的數學冒險。最後幾章將帶您解決一系列雜項問題，包括處理特定數據格式和加速代碼。

通過閱讀本書，您將擁有一系列實用的編碼解決方案，可用於解決計算數學和數據科學中的各種實際問題。

學到什麼：

- 熟悉用於解決數學問題的基本Python包、工具和庫
- 探索數學在現實世界中的應用，以減少優化問題
- 理解應用數學的核心概念及其在計算機科學中的應用
- 找出選擇最適合的包、工具或技術來解決問題的方法
- 使用Matplotlib實現基本的數學繪圖，更改繪圖風格並添加標籤
- 理解貝葉斯推斷和馬爾可夫鏈蒙特卡羅（MCMC）方法的概率理論

適合對象：

無論您是專業程序員還是學生，只要您想使用Python以計算方式解決數學問題，這本書都適合您。不需要高級數學能力，但基本的數學知識將有助於您充分利用這本Python數學書。假設您熟悉Python中的數據結構概念。