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Practical Discrete Mathematics

You're reading from   Practical Discrete Mathematics Discover math principles that fuel algorithms for computer science and machine learning with Python

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781838983147
Length 330 pages
Edition 1st Edition
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Authors (2):
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Ryan T. White Ryan T. White
Author Profile Icon Ryan T. White
Ryan T. White
Archana Tikayat Ray Archana Tikayat Ray
Author Profile Icon Archana Tikayat Ray
Archana Tikayat Ray
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Table of Contents (17) Chapters Close

Preface 1. Part I – Basic Concepts of Discrete Math
2. Chapter 1: Key Concepts, Notation, Set Theory, Relations, and Functions FREE CHAPTER 3. Chapter 2: Formal Logic and Constructing Mathematical Proofs 4. Chapter 3: Computing with Base-n Numbers 5. Chapter 4: Combinatorics Using SciPy 6. Chapter 5: Elements of Discrete Probability 7. Part II – Implementing Discrete Mathematics in Data and Computer Science
8. Chapter 6: Computational Algorithms in Linear Algebra 9. Chapter 7: Computational Requirements for Algorithms 10. Chapter 8: Storage and Feature Extraction of Graphs, Trees, and Networks 11. Chapter 9: Searching Data Structures and Finding Shortest Paths 12. Part III – Real-World Applications of Discrete Mathematics
13. Chapter 10: Regression Analysis with NumPy and Scikit-Learn 14. Chapter 11: Web Searches with PageRank 15. Chapter 12: Principal Component Analysis with Scikit-Learn 16. Other Books You May Enjoy

Searching Graph and Tree data structures

In the previous chapter, we learned about graphs and trees. As we progress through the chapter, keep in mind that whenever we refer to graphs, this includes trees because trees are simply graphs that have no cycles. The topic of this section is the idea of searching graphs. This simply means to travel along the edges of a graph to locate paths to destination vertices. This sounds like a simple thing to do, but we hope to do it as efficiently as we can because many real-world graphs are huge.

There are many reasons why we might want an algorithm to traverse the graph to find vertices. For example, suppose you want to send a message over the internet to five of your friends living in five different cities. There certainly will be no direct connection between your device and your friends' devices, so the message must follow multiple paths from vertex to vertex through networked devices until it reaches your friends. Networked devices connect...

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