Book Image

Applying Math with Python - Second Edition

By : Sam Morley
Book Image

Applying Math with Python - Second Edition

By: Sam Morley

Overview of this book

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.
Table of Contents (13 chapters)

Primer on calculus

Calculus is the study of functions and the way that they change. There are two major processes in calculus: differentiation and integration. Differentiation takes a function and produces a new function—called the derivative—that is the best linear approximation at each point. (You may see this described as the gradient of the function. Integration is often described as anti-differentiation—indeed, differentiating the integral of a function does give back the original function—but is also an abstract description of the area between the graph of the function and the axis, taking into account where the curve is above or below the axis.

Abstractly, the derivative of a function at a point is defined as a limit (which we won’t describe here) of the quantity:

This is because this small number becomes smaller and smaller. This is the difference in divided by the difference in , which is why the derivative...