A programmer's introduction to mathematics
Jeremy Kun (Author)
"A Programmer's Introduction to Mathematics uses your familiarity with ideas from programming and software to teach mathematics. You'll learn about the central objects and theorems of mathematics, including graphs, calculus, linear algebra, eigenvalues, optimization, and more. You'll also be immersed in the often unspoken cultural attitudes of mathematics, learning both how to read and write proofs while understanding why mathematics is the way it is. Between each technical chapter is an essay describing a different aspect of mathematical culture, and discussions of the insights and meta-insights that constitute mathematical intuition. As you learn, we'll use new mathematical ideas to create wondrous programs, from cryptographic schemes to neural networks to hyperbolic tessellations. Each chapter also contains a set of exercises that have you actively explore mathematical topics on your own. In short, this book will teach you to engage with mathematics. A Programmer's Introduction to Mathematics is written by Jeremy Kun, who has been writing about math and programming for 10 years on his blog "Math Intersect Programming." As of 2020, he works in datacenter optimization at Google.The second edition includes revisions to most chapters, some reorganized content and rewritten proofs, and the addition of three appendices." --Amazon website
Print Book, English, 2020
Second edition View all formats and editions
[CreateSpace Independent Publishing Platform], [Middletown, DE], 2020
iii, 385 pages : illustrations ; 25 cm
9798625373425
1378741664
Chapter 1. Like programming, mathematics has a culture
Chapter 2. Polynomials
Chapter 3. On pace and patience
Chapter 4. Sets
Chapter 5. Variable names, overloading, and your brain
Chapter 6. Graphs
Chapter 7. The many subcultures of mathematics
Chapter 8. Calculus with one variable
Chapter 9. On types and tail calls
Chapter 10. Linear algebra
Chapter 11. Live and learn linear algebra (again)
Chapter 12. Eigenvectors and eigenvalues
Chapter 13. Rigor and formality
Chapter 14. Multivariable calculus and optimization
Chapter 15. The argument for big-O notation
Chapter 16. Groups
Chapter 17. A new interface
Appendix A. Notation
Appendix B. A summary of proofs
Appendix C. Annotated resources
About the author and cover
Index