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

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781838983147

Length 330 pages

Edition 1st Edition

Languages

Python

Tools

NumPy

Concepts

Data Science

Authors (2):

Ryan T. White

Archana Tikayat Ray

View More author details

Table of Contents (17) Chapters

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

Leave a review - let other readers know what you think

Best-fit lines and the least-squares method

In this section, we will learn about best-fit lines and the least-squares method and see some very simple plots to enforce these concepts. Best-fit lines will be used to fit a dataset, and through doing this, it is made sure that the least-squares error is minimized.

Variable

A variable is a feature that does not have a fixed value. For example, let's say you want to buy a car and the most important feature for you is horsepower. You then go ahead and look at different car models to compare the horsepower values. Here the horsepower is a variable, since it takes different values based on the car model.

Linear relationship

Linear relationship is a term used to describe a straight-line relationship. This can be expressed mathematically as the equation of a line.

For example, if you are interested in finding the relationship between two variables, such as horsepower and weight, for different cars, and if the horsepower...