Book Image

Applying Math with Python

By : Sam Morley
Book Image

Applying Math with Python

By: Sam Morley

Overview of this book

Python, one of the world's most popular programming languages, has a number of powerful packages to help you tackle complex mathematical problems in a simple and efficient way. 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.
Table of Contents (12 chapters)

Working with polynomials and calculus

Polynomials are among the simplest functions in mathematics and are defined as a sum:

x represents a placeholder to be substituted, and ai is a number. Since polynomials are simple, they provide an excellent means for a brief introduction to calculus. Calculus concerns the differentiation and integration of functions. Integration is, roughly speaking, anti-differentiation, in the sense that first integrating and then differentiating yields the original function.

In this recipe, we will define a simple class that represents a polynomial and write methods for this class to perform differentiation and integration.

Getting ready

Geometrically, the derivative, obtained by differentiating, of a function is its gradient, and the integral, obtained by integrating, of a function is the area that lies between the curve of the function and the x axis, accounting for whether the curve lies above...