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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

In this chapter, we learned about the first steps toward performing any kind of statistical analysis: first, we defined our business problem and introduced the dataset. Based on the problem we wanted to solve, we prepared the dataset accordingly: we deleted some records, imputed missing values, transformed the types of some variables, and created new ones. Then we learned about the need for descriptive statistics; we learned how easy it is to calculate them using pandas and how to use and interpret those calculations. In the final section, we learned about how we can combine visualizations with descriptive statistics to get a deeper understanding of the relationships between variables in our datasets. What we learned in this chapter are concepts and techniques that you will be able to put in practice in any data analysis you perform. However, to get more sophisticated in your analysis, you need to have a good grasp of the basics of probability theory, which is the subject of...

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