Book Image

Practical Discrete Mathematics

By : Ryan T. White, Archana Tikayat Ray
Book Image

Practical Discrete Mathematics

By: Ryan T. White, Archana Tikayat Ray

Overview of this book

Discrete mathematics deals with studying countable, distinct elements, and its principles are widely used in building algorithms for computer science and data science. The knowledge of discrete math concepts will help you understand the algorithms, binary, and general mathematics that sit at the core of data-driven tasks. Practical Discrete Mathematics is a comprehensive introduction for those who are new to the mathematics of countable objects. This book will help you get up to speed with using discrete math principles to take your computer science skills to a more advanced level. As you learn the language of discrete mathematics, you’ll also cover methods crucial to studying and describing computer science and machine learning objects and algorithms. The chapters that follow will guide you through how memory and CPUs work. In addition to this, you’ll understand how to analyze data for useful patterns, before finally exploring how to apply math concepts in network routing, web searching, and data science. By the end of this book, you’ll have a deeper understanding of discrete math and its applications in computer science, and be ready to work on real-world algorithm development and machine learning.
Table of Contents (17 chapters)
1
Part I – Basic Concepts of Discrete Math
7
Part II – Implementing Discrete Mathematics in Data and Computer Science
12
Part III – Real-World Applications of Discrete Mathematics

Google PageRank I

In the late 1990s, there were many search engines on the internet, including Yahoo, Altavista, and Ask Jeeves, but when Google emerged in the early 2000s, it quickly supplanted all of those as the most popular search engine and has remained popular for nearly 20 years, in large part because its results were of such high quality that users flocked to the website. Google used a new approach to web searches that generated very good results.

Developed by Stanford University students, and later Google founders, Larry Page and Sergey Brin (along with researchers Rajeev Motwani and Terry Winograd) in 1996, the algorithm used was called PageRank. Google's primary searching algorithms have certainly progressed from this since 1996 but it remains a key part of their approach.

The key idea of PageRank is to not merely to look for websites that match the user's search terms most closely like most other search tools at the time but to weight the matches by the...