Math for Programmers

Math for Programmers
Author :
Publisher : Manning
Total Pages : 686
Release :
ISBN-10 : 9781617295355
ISBN-13 : 1617295353
Rating : 4/5 (353 Downloads)

Book Synopsis Math for Programmers by : Paul Orland

Download or read book Math for Programmers written by Paul Orland and published by Manning. This book was released on 2021-01-12 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore 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. 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 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. 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. Table of Contents 1 Learning math with code PART I - VECTORS AND GRAPHICS 2 Drawing with 2D vectors 3 Ascending to the 3D world 4 Transforming vectors and graphics 5 Computing transformations with matrices 6 Generalizing to higher dimensions 7 Solving systems of linear equations PART 2 - CALCULUS AND PHYSICAL SIMULATION 8 Understanding rates of change 9 Simulating moving objects 10 Working with symbolic expressions 11 Simulating force fields 12 Optimizing a physical system 13 Analyzing sound waves with a Fourier series PART 3 - MACHINE LEARNING APPLICATIONS 14 Fitting functions to data 15 Classifying data with logistic regression 16 Training neural networks


Math for Programmers Related Books

Essential Math for Data Science
Language: en
Pages: 352
Authors: Thomas Nield
Categories: Computers
Type: BOOK - Published: 2022-05-26 - Publisher: "O'Reilly Media, Inc."

GET EBOOK

Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, prob
Math for Programmers
Language: en
Pages: 686
Authors: Paul Orland
Categories: Computers
Type: BOOK - Published: 2021-01-12 - Publisher: Manning

GET EBOOK

Explore important mathematical concepts through hands-on coding. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning
Foundations of Data Science
Language: en
Pages: 433
Authors: Avrim Blum
Categories: Computers
Type: BOOK - Published: 2020-01-23 - Publisher: Cambridge University Press

GET EBOOK

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and a
Mathematics for Machine Learning
Language: en
Pages: 392
Authors: Marc Peter Deisenroth
Categories: Computers
Type: BOOK - Published: 2020-04-23 - Publisher: Cambridge University Press

GET EBOOK

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, opti
Practical Statistics for Data Scientists
Language: en
Pages: 322
Authors: Peter Bruce
Categories: Computers
Type: BOOK - Published: 2017-05-10 - Publisher: "O'Reilly Media, Inc."

GET EBOOK

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics r