num_pages: 677
description: "A gentle introduction to some of the most useful mathematical concepts that should be in your developer toolbox." - Christopher Haupt, New RelicExplore important mathematical concepts through hands-on coding. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.Filled with graphics and more than 300 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.SummaryTo 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 technologySkip the mathematical 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!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 classificationAbout the readerFor programmers with basic skills in algebra.About the authorPaul 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.Table of Contents1 Learning math with codePART I - VECTORS AND GRAPHICS2 Drawing with 2D vectors3 Ascending to the 3D world4 Transforming vectors and graphics5 Computing transformations with matrices6 Generalizing to higher dimensions7 Solving systems of linear equationsPART 2 - CALCULUS AND PHYSICAL SIMULATION8 Understanding rates of change9 Simulating moving objects10 Working with symbolic expressions11 Simulating force fields12 Optimizing a physical system13 Analyzing sound waves with a Fourier seriesPART 3 - MACHINE LEARNING APPLICATIONS14 Fitting functions to data15 Classifying data with logistic regression16 Training neural networks
language: English
title: Math for Programmers: 3D graphics, machine learning, and simulations with Python
publisher: Manning