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)

Further reading

A good textbook on regression in statistics is the book Probability and Statistics by Mendenhall, Beaver, and Beaver, as mentioned in Chapter 6, Working with Data and Statistics. The following books provide a good introduction to classification and regression in modern data science:

  • James, G. and Witten, D., 2013. An Introduction To Statistical Learning: With Applications In R. New York: Springer.
  • Müller, A. and Guido, S., 2016. Introduction To Machine Learning With Python. Sebastopol: O’Reilly Media.

A good introduction to time series analysis can be found in the following book:

  • Cryer, J. and Chan, K., 2008. Time Series Analysis. New York: Springer.