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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

Product type Paperback

Published in Aug 2020

Publisher Packt

ISBN-13 9781800209763

Length 740 pages

Edition 1st Edition

Languages

Python

Concepts

Artificial Intelligence

Authors (6):

Ajinkya Sudhir Kolhe

Quan Nguyen

Marios Tsatsos

Alexander Joseph Sarver

Peter Farrell

Alvaro Fuentes

+2 more

View More author details

Table of Contents (14) Chapters

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

This chapter introduced the most fundamental building blocks of Python programming: control flow, data structures, algorithm design, and various house-keeping tasks (debugging, testing, and version control). The knowledge that we have gained in this chapter will prepare us for discussions in future chapters, where we'll learn about other more complex and specialized tools in Python. In particular, in the next chapter, we will talk about the main tools and libraries that Python offers in the fields of statistics, scientific computing, and data science.

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Authors (6)

Peter Farrell

Peter Farrell

Peter Farrell learned to program from the Logo code in Seymour Paperts Mindstorms. A student introduced him to Python and he never looked back. In 2015, he self-published Hacking Math Class with Python on applying Python programming to learning and teaching high-school math. In 2019, No Starch Press published his second book, Math Adventures with Python. In his books, he also presents 21st-century topics, such as Cellular Automata, 3D Graphics, and Genetic Algorithms. Currently, he teaches Python and Math in the Dallas, Texas area.

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Marios Tsatsos

Marios Tsatsos

Marios Tsatsos has 8+ years of experience in research in Physics, analytical thinking, modeling, problem solving and decision making.

See other products by Marios Tsatsos

Alexander Joseph Sarver

Alexander Joseph Sarver

Alexander Joseph Sarver is an ambitious data scientist and content creator with 6 years of mathematical teaching experience.

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Ajinkya Sudhir Kolhe

Ajinkya Sudhir Kolhe

Ajinkya Sudhir Kolhe is a programmer working for a tech company in the Bay area. He holds a M.S. in Computer Science and has experience in the tech industry of 5+ years. His area of interests include problem solving, analytics and applications in Python.

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Quan Nguyen

Quan Nguyen

Quan Nguyen, the author of the first edition of this book, is a Python programmer with a strong passion for machine learning. He holds a dual degree in mathematics and computer science, with a minor in philosophy, earned from DePauw University. Quan is deeply involved in the Python community and has authored multiple Python books, contributing to the Python Software Foundation and regularly sharing insights on DataScience portal. He is currently pursuing a Ph.D. in computer science at Washington University in St. Louis.

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Alvaro Fuentes

Alvaro Fuentes

Alvaro Fuentes is a senior data scientist with a background in applied mathematics and economics. He has more than 14 years of experience in various analytical roles and is an analytics consultant at one of the ‘Big Three' global management consulting firms, leading advanced analytics projects in different industries like banking, technology, and consumer goods. Alvaro is also an author and trainer in analytics and data science and has published courses and books, such as 'Become a Python Data Analyst' and 'Hands-On Predictive Analytics with Python'. He has also taught data science and related topics to thousands of students both on-site and online through different platforms such as Springboard, Simplilearn, Udemy, and BSG Institute, among others.

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