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 reader
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.
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A gentle introduction to some of the most useful mathematical concepts that should be in your developer toolbox.
A rigorous yet approachable overview of the mathematics that underpin a number of modern programming domains.
Engaging, practical, recommend for all levels.
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.
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