What this book covers
Chapter 1, An Introduction to Basic Packages, Functions, and Concepts, introduces some of the basic tools and concepts that will be needed in the rest of the book, including the main Python packages for mathematical programming, NumPy and SciPy.
Chapter 2, Mathematical Plotting with Matplotlib, covers the basics of plotting with Matplotlib, which is useful when solving almost all mathematical problems.
Chapter 3, Calculus and Differential Equations, introduces topics from calculus such as differentiation and integration, and some more advanced topics such as ordinary and partial differential equations.
Chapter 4, Working with Randomness and Probability, introduces the fundamentals of randomness and probability, and how to use Python to explore these ideas.
Chapter 5, Working with Trees and Networks, covers working with trees and networks (graphs) in Python using the NetworkX package.
Chapter 6, Working with Data and Statistics, gives various techniques for handling, manipulating, and analyzing data using Python.
Chapter 7, Using Regression and Forecasting, describes various techniques for modeling data and predicting future values using the Statsmodels package and scikit-learn.
Chapter 8, Geometric Problems, demonstrates various techniques for working with geometric objects in Python using the Shapely package.
Chapter 9, Finding Optimal solutions, introduces optimization and game theory, which uses mathematical methods to find the best solutions to problems.
Chapter 10, Increasing your Productivity, covers an assortment of situations you might encounter while solving mathematical problems using Python.
