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Practical Discrete Mathematics

You're reading from  Practical Discrete Mathematics

Product type Book
Published in Feb 2021
Publisher Packt
ISBN-13 9781838983147
Pages 330 pages
Edition 1st Edition
Languages
Authors (2):
Ryan T. White Ryan T. White
Profile icon Ryan T. White
Archana Tikayat Ray Archana Tikayat Ray
Profile icon Archana Tikayat Ray
View More author details
Toc

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 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

Summary

In this chapter, we primarily discussed how to count the cardinality, or size, of sets of different types. First, we looked at counting Cartesian products, where we take one element from each of a sequence of sets to create a new set. Counting the size of these comes down to the fundamental counting rule, which we used to count binary structures and the colors that can be displayed with HTML/CSS.

Second, we looked at permutations and combinations using factorials (for permutations) and binomial coefficients (for combinations), which we derived directly from the fundamental counting rule. For factorials, the key tool in Python is the factorial function in the math library and, for binomial coefficients, the binom function from the SciPy library.

Lastly, we took a look at just a few applications of combinatorics in computer science, including memory allocation, the (poor) speed of brute-force algorithms in a few examples in the area of cryptology, and for a classical optimization...

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