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#### Overview of this book

Are you looking to start developing artificial intelligence applications? Do you need a refresher on key mathematical concepts? Full of engaging practical exercises, The Statistics and Calculus with Python Workshop will show you how to apply your understanding of advanced mathematics in the context of Python. The book begins by giving you a high-level overview of the libraries you'll use while performing statistics with Python. As you progress, you'll perform various mathematical tasks using the Python programming language, such as solving algebraic functions with Python starting with basic functions, and then working through transformations and solving equations. Later chapters in the book will cover statistics and calculus concepts and how to use them to solve problems and gain useful insights. Finally, you'll study differential equations with an emphasis on numerical methods and learn about algorithms that directly calculate values of functions. By the end of this book, you’ll have learned how to apply essential statistics and calculus concepts to develop robust Python applications that solve business challenges.
Preface
1. Fundamentals of Python
Free Chapter
2. Python's Main Tools for Statistics
3. Python's Statistical Toolbox
4. Functions and Algebra with Python
5. More Mathematics with Python
6. Matrices and Markov Chains with Python
7. Doing Basic Statistics with Python
8. Foundational Probability Concepts and Their Applications
9. Intermediate Statistics with Python
10. Foundational Calculus with Python
11. More Calculus with Python
12. Intermediate Calculus with Python

# Summary

The tools of calculus allowed mathematicians and scientists to deal with constantly changing values, and those tools changed the way science is done. All of a sudden, we could use infinitely small steps to approximate the slope of a curve at a point, or infinitely small rectangles to approximate the area under a curve. These tools were developed hundreds of years before our modern world of computers and free programming software, but there's no reason to limit ourselves to the tools available to Newton, Leibniz, and the Bernoullis.

In this chapter, we learned to take derivatives of functions by simply dividing the rise of the function from one point to another by the infinitesimal run between those points. We simply told Python to divide 1 by a million to give us that small number. Without a computer, plugging those decimals into a function would be a daunting task, but Python plugs a decimal into a function as easily as a whole number.

We used the derivative idea...