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The Statistics and Calculus with Python Workshop

You're reading from  The Statistics and Calculus with Python Workshop

Product type Book
Published in Aug 2020
Publisher Packt
ISBN-13 9781800209763
Pages 740 pages
Edition 1st Edition
Languages
Concepts
Authors (6):
Peter Farrell Peter Farrell
Profile icon Peter Farrell
Alvaro Fuentes Alvaro Fuentes
Profile icon Alvaro Fuentes
Ajinkya Sudhir Kolhe Ajinkya Sudhir Kolhe
Profile icon Ajinkya Sudhir Kolhe
Quan Nguyen Quan Nguyen
Profile icon Quan Nguyen
Alexander Joseph Sarver Alexander Joseph Sarver
Profile icon Alexander Joseph Sarver
Marios Tsatsos Marios Tsatsos
Profile icon Marios Tsatsos
View More author details

Table of Contents (14) Chapters

Preface
1. Fundamentals of Python 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 Appendix

6. Matrices and Markov Chains with Python

Activity 6.01: Building a Text Predictor Using a Markov Chain

Solution:

There are a few ways to approach this problem, and it is worth mentioning that the approach we will be taking is perhaps the easiest way in which text prediction is used. In actual practice, text predictions are far more complicated and have many other factors that affect them, which we will briefly cover at the end of the activity.

  1. We will be using the transcript of the speech given by Winston Churchill at the House of Commons after the soldiers of the Allied forces were rescued from Dunkirk during World War II. The speech by itself is worth a read and can be easily found online if you are interested.

    Note

    You can download the transcript from https://packt.live/38rZy6v .

  2. This list is stored in a text file named churchill.txt. Read through that text file:
    # Churchill's speech
    churchill = open('churchill.txt').read()
    keywords = churchill.split...
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