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The Statistics and Calculus with Python Workshop

You're reading from   The Statistics and Calculus with Python Workshop A comprehensive introduction to mathematics in Python for artificial intelligence applications

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781800209763
Length 740 pages
Edition 1st Edition
Languages
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Authors (6):
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Ajinkya Sudhir Kolhe Ajinkya Sudhir Kolhe
Author Profile Icon Ajinkya Sudhir Kolhe
Ajinkya Sudhir Kolhe
Quan Nguyen Quan Nguyen
Author Profile Icon Quan Nguyen
Quan Nguyen
Marios Tsatsos Marios Tsatsos
Author Profile Icon Marios Tsatsos
Marios Tsatsos
Alexander Joseph Sarver Alexander Joseph Sarver
Author Profile Icon Alexander Joseph Sarver
Alexander Joseph Sarver
Peter Farrell Peter Farrell
Author Profile Icon Peter Farrell
Peter Farrell
Alvaro Fuentes Alvaro Fuentes
Author Profile Icon Alvaro Fuentes
Alvaro Fuentes
+2 more Show less
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Table of Contents (14) Chapters Close

Preface
1. Fundamentals of Python 2. Python's Main Tools for Statistics FREE CHAPTER 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 Appendix

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...

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