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The nature of code : simulating natural systems with JavaScript

By: Shiffman, Daniel.
Publisher: San Francisco : No Starch Press, 2024Description: xxxviii, 602 p. ; ill., 24 cm.ISBN: 9781718503700.Subject(s): Computer Graphics | JavaScript | Popularization | Angular acceleration | Dot product | Neural network | Newton's second law | Particle system | Perlin noiseDDC classification: 005.2762 Summary: What if you could re-create the awe-inspiring flocking patterns of birds or the hypnotic dance of fireflies—with code? For over a decade, The Nature of Code has empowered countless readers to do just that, bridging the gap between creative expression and programming. This innovative guide by Daniel Shiffman, creator of the beloved Coding Train, welcomes budding and seasoned programmers alike into a world where code meets playful creativity. This JavaScript-based edition of Shiffman’s groundbreaking work gently unfolds the mysteries of the natural world, turning complex topics like genetic algorithms, physics-based simulations, and neural networks into accessible and visually stunning creations. 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. All examples are written with p5.js, a JavaScript library for creative coding.
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005.2762 SHI (Browse shelf) Available 035606

Includes index.

What if you could re-create the awe-inspiring flocking patterns of birds or the hypnotic dance of fireflies—with code? For over a decade, The Nature of Code has empowered countless readers to do just that, bridging the gap between creative expression and programming. This innovative guide by Daniel Shiffman, creator of the beloved Coding Train, welcomes budding and seasoned programmers alike into a world where code meets playful creativity. This JavaScript-based edition of Shiffman’s groundbreaking work gently unfolds the mysteries of the natural world, turning complex topics like genetic algorithms, physics-based simulations, and neural networks into accessible and visually stunning creations. 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. All examples are written with p5.js, a JavaScript library for creative coding.

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