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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

Using graphs, trees, and networks

Graphs and the other similar structures we introduced in the previous section are versatile modeling tools. This section will be an overview of some of the most common areas where these structures are used in discrete mathematics. Note that some of these topics will be explored much more deeply in some forthcoming chapters.

In Chapter 9, Searching Data Structures and Finding Shortest Paths, we will learn how to search graphs (especially trees) to find certain features or characteristics. One application of these searches is in scheduling problems. For example, consider a directed graph where each vertex represents a task that needs to be done to complete a large project where a directed edge between task A and task B means task A must be completed before task B. In other words, the directed edge represents a dependency.

Clearly, there should be no cycles since that would lead to an infinite loop of tasks to complete! This means the directed graph...

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