Paul Orland

Math for Programmers (eBook, ePUB)

3D graphics, machine learning, and simulations with Python

• Format: ePub

Produktbeschreibung

Explore important mathematical concepts through hands-on coding. Purchase includes free PDF and ePub versions 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. Summary 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! 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

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Simon + Schuster LLC
• Seitenzahl: 688
• Erscheinungstermin: 30. November 2020
• Englisch
• ISBN-13: 9781638357070
• Artikelnr.: 62084931

Autorenporträt

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.

Inhaltsangabe

table of contents
READ IN LIVEBOOK1LEARNING MATH WITH CODE
PART 1: VECTORS AND GRAPHICS
READ IN LIVEBOOK2DRAWING WITH 2D VECTORS
READ IN LIVEBOOK3ASCENDING TO THE 3D WORLD
READ IN LIVEBOOK4TRANSFORMING VECTORS AND GRAPHICS
READ IN LIVEBOOK5COMPUTING TRANSFORMATIONS WITH MATRICES
READ IN LIVEBOOK6GENERALIZING TO HIGHER DIMENSIONS
READ IN LIVEBOOK7SOLVING SYSTEMS OF LINEAR EQUATIONS
PART 2: CALCULUS AND PHYSICAL SIMULATION
READ IN LIVEBOOK8UNDERSTANDING RATES OF CHANGE
READ IN LIVEBOOK9SIMULATING MOVING OBJECTS
READ IN LIVEBOOK10WORKING WITH SYMBOLIC EXPRESSIONS
READ IN LIVEBOOK11SIMULATING FORCE FIELDS
READ IN LIVEBOOK12OPTIMIZING A PHYSICAL SYSTEM
READ IN LIVEBOOK13ANALYZING SOUND WAVES WITH A FOURIER SERIES
PART 3: MACHINE LEARNING APPLICATIONS
READ IN LIVEBOOK14FITTING FUNCTIONS TO DATA
READ IN LIVEBOOK15CLASSIFYING DATA WITH LOGISTIC REGRESSION
READ IN LIVEBOOK16TRAINING NEURAL NETWORKS
APPENDIXES
READ IN LIVEBOOKAPPENDIX A: GETTING SET UP WITH PYTHON
READ IN LIVEBOOKAPPENDIX B: PYTHON TIPS AND TRICKS
READ IN LIVEBOOKAPPENDIX C: LOADING AND RENDERING 3D MODELS WITH OPENGL AND
PYGAME