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Math for Programming

by Ronald T. Kneusel
October 2024, 450 pp.
ISBN-13: 
9781718503588
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This book summarizes all the core mathematical topics a typical professional software engineer needs to know. In condensing the various concepts covered in an undergraduate computer science program into a single volume, it provides an excellent starting point for independent study, or a refresher for those who haven’t been in a classroom for years. Early chapters cover preliminary subjects like number representation systems, set theory, and Boolean algebra, followed by a dive into the field of discrete mathematics, including functions, induction proofs, number theory, combinatorics, graphs, and trees. Later sections examine essential topics in probability, statistics, linear algebra, and calculus.

Rather than confine itself to abstract theory, the book focuses on practical applications and numerical methods at the level typically encountered by working software developers. In addition, hands-on code examples in Python and C make the topics concrete.

Author Bio 

Ronald T. Kneusel is a data scientist who builds deep-learning (AI) systems, as well as extensive experience with medical imaging and the development of medical devices. He earned a PhD in machine learning from the University of Colorado, Boulder, has nearly 20 years of machine learning experience in industry, and is presently pursuing deep-learning projects with L3Harris Technologies, Inc. Kneusel is also the author of Random Numbers and Computers (Springer 2018), in addition to Math for Deep Learning, Practical Deep Learning, and Strange Code—all published by No Starch Press.

Table of contents 

Introduction
Chapter 1. Computers and Numbers
Chapter 2. Sets and Abstract Algebra
Chapter 3. Boolean Algebra
Chapter 4. Functions and Relations
Chapter 5. Induction
Chapter 6. Recurrence and Recursion
Chapter 7. Number Theory
Chapter 8. Counting and Combinatorics
Chapter 9. Graphs
Chapter 10. Trees
Chapter 11. Probability
Chapter 12. Statistics
Chapter 13. LinearAlgebra
Chapter 14. More Linear Algebra
Chapter 15. Differential Calculus
Chapter 16. Integral Calculus
Chapter 17. Differential Equations

The chapters in red are included in this Early Access PDF.