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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
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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

Area of a Surface

Let's learn how to take this from two to three dimensions and calculate the area of a 3D surface. In Chapter 10, Foundational Calculus with Python, we learned how to calculate the area of a surface of revolution, but this is a surface where the third dimension, z, is a function of the values of x and y.

The Formulas

The traditional, algebraic way to solve this analytically is given by a double integral over a surface:

Figure 11.18: Formula to calculate area of a surface

Here, z = f(x,y) or (x,y,f(x,y)). Those curly d's are deltas, meaning we'll be dealing with partial derivatives. Partial derivatives are derivatives but only with respect to one variable, even if the function is dependent on more than one variable. Here's a function that returns the partial derivative of a function, f, with respect to a variable, u, at a specific point (v,w). Depending on which variable we're interested in, x or y, the function...

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