Discrete Mathematics: An open Introduction by Oscar Levin is a free open source textbook that covers essential mathematics useful for data science, machine learning and other programming professionals.

The book is endorsed by the American Institute of Mathematics' Open Textbook Initiative and was given the best review by the Open Textbook Library.

Discrete mathematics comprises set theory, graphs, logic, trees, algorithms and a lot more topics that are essential in data science problem-solving. As we are aware the Maths and programming goes hand in hand. That too in data science and machine learning, mathematical models play a vital role in obtaining the solution to the business problem. This book is one such absolute guide for every data science professional, that comes as a free open resource.

Let's look into the contents of the book.

Table of Contents

• Introduction and Preliminaries about Discrete Mathematics

• Counting Principles

• Descriptions of Sequences

• Symbolic logic and Proofs

• Graph Theory

• Additional Topics on Generating Functions and Number Theory

The above book is available in three formats, the free online interactive format the offline free PDF format and the paperback version on Amazon that is very cost-effective.

GitHub Reference: Discrete Mathematics

These are the topics and areas of discrete mathematics covered in this definitive guide. Do make the best use of it to soar high in your data science career!