How can we use code to capture the unpredictable properties of nature? How can understanding the mathematical principles behind our physical world help us create interesting digital environments? Written by 'The Coding Train' YouTube star Daniel Shiffman, The Nature of Code is a beginner-friendly creative coding tutorial that explores a range of programming strategies for developing computer simulations of natural systems - from elementary concepts in math and physics to sophisticated machine-learning algorithms. Using the same enthusiastic style on display in Shiffman's popular YT channel, this book makes learning to program fun, empowering you to generate fascinating graphical output while refining your problem-solving and algorithmic-thinking skills. You'll progress from building a basic physics engine that simulates the effects of forces like gravity and wind resistance, to creating evolving systems of intelligent autonomous agents that can learn from their mistakes and adapt to their environment. The Nature of Code introduces important topics such as: Randomness, forces and vectors, trigonometry, cellular automata and fractals, genetic algorithms, neural networks. Learn from an expert how to transform your beginner-level skills into writing well-organized, thoughtful programs that set the stage for further experiments in generative design.
Rezensionen / Stimmen
"Fred Rogers, Ted Lasso, Dan Shiffman. These are the people I want to emulate, to learn from, and to look up to. The Nature of Code is an incredibly deep but shockingly accessible overview of the JavaScript Language and the incredible mind of Dan Shiffman. What a joy to explore both!"
-Scott Hanselman, VP Developer Community, Microsoft
"What a way to explain the complex! Dan has always had a knack for making the difficult seem easy on his wonderfully successful YouTube channel. Things are equally as wonderful in his book. The hands-on approach he encourages students to take before jumping into detailed analysis builds curiosity in any problem solver."
-Ania Kubow, @aniakubow, Software Developer and Course Creator on "Code with Ania Kubow"
"I learned p5.js from Dan on The Coding Train. I remember the first time this happy bearded guy danced onto the screen... I fell down the rabbithole quickly and was hooked on Dan's love of teaching, his dedication to making it fun, and his ability to distill complexity into simple concepts. The website for this book is especially impressive, with interactive and editable examples throughout. I can't recommend this (and Dan!) highly enough."
-Josh Sowin, founder at Hypertext Foundation
"Thanks to The Nature of Code, I've discovered just how creative, experimental, and enjoyable coding can be. This book complements Dan's popular YouTube channel, "The Coding Train," providing a seamless learning experience for those who enjoy visual and interactive content. It is a must-have for anyone looking to dive into the realm of creative coding!"
-Patt Vira, Creative Coder & Content Creator @pattvira
"A wonderful exploration of natural systems using approachable, witty, and smart examples that any programmer can read and implement on their own. Conversational and engaging, Dan has hit another home run with this one!"
-Rob Conery, author of The Imposter's Handbook
Sprache
Verlagsort
Produkt-Hinweis
Maße
Höhe: 238 mm
Breite: 186 mm
Dicke: 38 mm
Gewicht
ISBN-13
978-1-7185-0370-0 (9781718503700)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Daniel Shiffman, creator of the YouTube channel The Coding Train (www.youtube.com/c/TheCodingTrain), spends much of his free time teaching nearly 2 million subscribers how to code through a blend of step-by-step tutorials and project videos. An associate arts professor at the NYU Tisch School of the Arts and co-founder of the Processing Foundation, Shiffman is on a mission to empower curious learners and humans everywhere to express themselves through code.
Acknowledgments
Introduction
Chapter 0: Randomness
Chapter 1: Vectors
Chapter 2: Forces
Chapter 3: Oscillation
Chapter 4: Particle Systems
Chapter 5: Autonomous Agents
Chapter 6: Physics Libraries
Chapter 7: Cellular Automata
Chapter 8: Fractals
Chapter 9: Evolutionary Computing
Chapter 10: Neural Networks
Chapter 11: Neuroevolution
Appendix: Creature Design Tutorial
Image Credits
Index
