Math for Programmers
3D graphics, machine learning, and simulations with Python
Paul Orland
  • MEAP began December 2018
  • Publication in January 2021 (estimated)
  • ISBN 9781617295355
  • 688 pages (estimated)
  • printed in black & white

Tackles a rarely discussed area of upskilling for the modern developer; this book is vital for the community to have access to.

James Nyika
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

Most businesses realize they need to apply data science and effective machine learning to gain and maintain a competitive edge. To build these applications, they need developers comfortable writing code and using tools steeped in statistics, linear algebra, and calculus. Math also plays an integral role in other modern applications like game development, computer graphics and animation, image and signal processing, pricing engines, and stock market analysis. Whether you’re a self-taught programmer without a core university math foundation or you just need to rekindle the glowing math embers, this book is a great way to fire up your skills.

About the book

Math for Programmers teaches you to solve mathematical problems in code. Thanks to the author’s fun and engaging style, you’ll enjoy thinking about math like a programmer. With accessible examples, scenarios, and exercises perfect for the working developer, you’ll start by exploring functions and geometry in 2D and 3D. With those basic building blocks behind you, you’ll move into the bread and butter math for machine learning and game programming, including matrices and linear transformations, derivatives and integrals, differential equations, probability, classification algorithms, and more. Don’t worry if it sounds intimidating or, worse yet, boring! Coder and mathematician Paul Orland makes learning these vital concepts painless, relevant, and fun!

Real-world examples in this practical tutorial include building and rendering 3D models, animations with matrix transformations, manipulating images and sound waves, and building a physics engine for a video game. Along the way, you’ll test yourself with lots of exercises to ensure you’ve got a firm grasp of the concepts. Hands-on mini-projects throughout lock in all you’ve learned. When you’re done, you’ll have a solid foundation of the math skills essential in today’s most popular tech trends.

What's inside

  • 2D and 3D vector math
  • Matrices and linear transformations
  • Core concepts from linear algebra
  • Calculus with one or more variables
  • Algorithms for regression, classification, and clustering
  • Interesting real-world examples
  • More than 200 exercises and mini-projects

About the reader

Written for programmers with solid algebra skills (even if they need some dusting off). No formal coursework in linear algebra or calculus is required.

About the author

Paul Orland is CEO of Tachyus, a Silicon Valley startup building predictive analytics software to optimize energy production in the oil and gas industry. As founding CTO, he led the engineering team to productize hybrid machine learning and physics models, distributed optimization algorithms, and custom web-based data visualizations. He has a B.S. in mathematics from Yale University and a M.S. in physics from the University of Washington.

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