The Nature of Code

All aboard The Coding Train! This beginner-friendly creative coding tutorial is designed to grow your skills in a fun, hands-on way as you build simulations of real-world phenomena with "The Coding Train" YouTube star Daniel Shiffman.

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.

NOTE: All examples are written with p5.js, a JavaScript library for creative coding, and are available on the book's website.

《The Coding Train》全體上船！這本適合初學者的創意編程教程旨在通過與「The Coding Train」YouTube明星Daniel Shiffman一起建立真實世界現象的模擬來提升你的技能，並以有趣的、實踐的方式進行。

我們如何使用代碼捕捉自然的不可預測特性？了解我們物理世界背後的數學原理如何幫助我們創建有趣的數字環境？《The Nature of Code》由「The Coding Train」YouTube明星Daniel Shiffman撰寫，是一本適合初學者的創意編程教程，探索了一系列用於開發計算機模擬自然系統的編程策略，從數學和物理的基本概念到複雜的機器學習算法。

這本書以Shiffman在其受歡迎的YouTube頻道中展示的同樣熱情的風格，讓學習編程變得有趣，使你能夠生成迷人的圖形輸出，同時完善你的問題解決和算法思維能力。你將從構建一個基本的物理引擎開始，模擬重力和風阻等力的效果，進而創建智能自主代理系統的演化系統，這些系統可以從錯誤中學習並適應環境。

《The Nature of Code》介紹了一些重要的主題，包括：
- 隨機性
- 力和向量
- 三角學
- 細胞自動機和分形
- 遺傳算法
- 神經網絡

從專家那裡學習如何將你的初級技能轉化為撰寫組織良好、思考周全的程序，為生成設計的進一步實驗奠定基礎。

注意：所有示例均使用p5.js編寫，這是一個用於創意編程的JavaScript庫，並可在本書的網站上獲得。

Daniel Shiffman is an Associate Arts Professor at ITP/IMA, Tisch School of the Arts, NYU. He is a director of The Processing Foundation and the author of Learning Processing: A Beginner's Guide to Programming Images, Animation, and Interaction and The Nature of Code, an open source book about simulating natural phenomenon with code. On his YouTube channel, The Coding Train, he publishes "creative coding" tutorials with subjects ranging from the basics of programming languages like JavaScript (with p5.js) and Java (with Processing) to generative algorithms like physics simulation, computer vision, and data visualization.

Daniel Shiffman 是紐約大學 Tisch School of the Arts 的 ITP/IMA 藝術副教授。他是 Processing Foundation 的主管，也是《Learning Processing: A Beginner's Guide to Programming Images》、《Animation》和《The Nature of Code》的作者。《The Nature of Code》是一本開源書籍，介紹如何使用程式碼模擬自然現象。在他的 YouTube 頻道 The Coding Train 上，他發佈了各種「創意編程」教學，主題涵蓋從 JavaScript (使用 p5.js) 和 Java (使用 Processing) 的基礎程式語言教學，到生成算法如物理模擬、電腦視覺和數據可視化等。