Math for Programming

Math for Programming by Ronald T. Kneusel is a comprehensive guide designed to equip software developers with the essential mathematical tools needed for effective programming. Spanning 504 pages, this book delves into core mathematical concepts and demonstrates their practical applications in software development.

📘 Overview

Whether you're optimizing search algorithms, building physics engines for games, or training neural networks, success hinges on a solid understanding of mathematics This book provides a structured approach to mastering the math that underpins modern programming challenges

🧠 Key Topics Covered

• Discrete Mathematics Explore sets, Boolean algebra, functions, relations, induction, recursion, number theory, combinatorics, graphs, and tree.
• Linear Algebra Learn how vectors and matrices facilitate efficient data manipulatio.
• Calculus Understand how differential and integral calculus drive optimization and simulation.
• Probability & Statistics Apply concepts to model uncertainty and analyze dat.
• Differential Equations Solve dynamic problems commonly encountered in simulations and modeling.

💻 Practical Approach

Each chapter includes clear explanations and practical examples, with code snippets in Python and C to illustrate the application of mathematical concepts in real-world programming scenarios

👨‍🏫 About the Autor

Ronald T. Kneusel is a seasoned data scientist with extensive experience in machine learning and deep learning. He holds a PhD in machine learning from the University of Colorado, Boulder, and has been active in the field since 03. Kneusel is also the author of several other works, including Practical Deep Learning, Math for Deep Learning, The Art of Randomness, How AI Works, and Strange Code, all published by No Starch Press

📚 Table of Contents

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

Math for Programming serves as an invaluable resource for anyone looking to strengthen their mathematical foundation and apply these principles to enhance their programming sills.