Video description
A gentle introduction to some of the most useful mathematical concepts that should be in your developer toolbox.
Christopher Haupt, New Relic
To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest programming fields.
about the technology
Skip the mathematical jargon: This one-of-a-kind book uses Python to teach the math you need to build games, simulations, 3D graphics, and machine learning algorithms. Discover how algebra and calculus come alive when you see them in code!
about the book
In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications.
what's inside
- Vector geometry for computer graphics
- Matrices and linear transformations
- Core concepts from calculus
- Simulation and optimization
- Image and audio processing
- Machine learning algorithms for regression and classification
about the audience
For programmers with basic skills in algebra.
about the author
Paul Orland is a programmer, software entrepreneur, and math enthusiast. He is co-founder of Tachyus, a start-up building predictive analytics software for the energy industry. You can find him online at www.paulor.land
A rigorous yet approachable overview of the mathematics that underpin a number of modern programming domains.
Dan Sheikh, BCG Digital Ventures
Engaging, practical, recommend for all levels.
Vincent Zhu, rethinkxsocial.com
It provides a bridge for programmers who need to brush up on their math skills, and does a nice job of making the math less mysterious and more approachable.
Robert Walsh, Excalibur Solutions
NARRATED BY DEREK LETTMAN
Table of Contents
Chapter 1. Learning math with code
Part 1. Vectors and graphics
Chapter 2. Drawing with 2D vectors
Chapter 3. Ascending to the 3D world
Chapter 4. Transforming vectors and graphics
Chapter 5. Computing transformations with matrices
Chapter 6. Generalizing to higher dimensions
Chapter 7. Solving systems of linear equations
Part 2. Calculus and physical simulation
Chapter 8. Understanding rates of change
Chapter 9. Simulating moving objects
Chapter 10. Working with symbolic expressions
Chapter 11. Simulating force fields
Chapter 12. Optimizing a physical system
Chapter 13. Analyzing sound waves with a Fourier series
Part 3. Machine learning applications
Chapter 14. Fitting functions to data
Chapter 15. Classifying data with logistic regression
Chapter 16. Training neural networks
Appendix B. Python tips and tricks