The Art of Randomness: Randomized Algorithms in the Real World

Harness the power of randomness (and Python code) to solve real-world problems in fun, hands-on experiments--from simulating evolution to encrypting messages to making machine-learning algorithms!

The Art of Randomness is a hands-on guide to mastering the many ways you can use randomized algorithms to solve real programming and scientific problems. You'll learn how to use randomness to run simulations, hide information, design experiments, and even create art and music. All you need is some Python, basic high school math, and a roll of the dice.

Author Ronald T. Kneusel focuses on helping you build your intuition so that you'll know when and how to use random processes to get things done. You'll develop a randomness engine (a Python class that supplies random values from your chosen source), then explore how to leverage randomness to:

• Simulate Darwinian evolution and optimize with swarm-based search algorithms
• Design scientific experiments to produce more meaningful results by making them truly random
• Implement machine learning algorithms like neural networks and random forests
• Use Markov Chain Monte Carlo methods to sample from complex distributions
• Hide information in audio files and images, generate art, and create music
• Reconstruct original signals and images from only randomly sampled data

Scientific anecdotes and code examples throughout illustrate how randomness plays into areas like optimization, machine learning, and audio signals. End-of-chapter exercises encourage further exploration.

Whether you're a programmer, scientist, engineer, mathematician, or artist, you'll find The Art of Randomness to be your ticket to discovering the hidden power of applied randomness and the ways it can transform your approach to solving problems, from the technical to the artistic.

發揮隨機性的力量（和 Python 程式碼），以有趣的實驗解決現實世界的問題——從模擬進化到加密訊息，再到製作機器學習演算法！《隨機性的藝術》是一本實踐指南，教你如何運用隨機演算法解決真實的程式設計和科學問題。你將學習如何使用隨機性進行模擬、隱藏資訊、設計實驗，甚至創作藝術和音樂。你只需要一些 Python 程式語言、基礎的高中數學和一個骰子。

作者 Ronald T. Kneusel 的重點是幫助你建立直覺，讓你知道何時以及如何使用隨機過程來完成任務。你將開發一個隨機性引擎（一個提供從你選擇的來源獲取隨機值的 Python 類），然後探索如何利用隨機性來：
- 模擬達爾文進化並使用基於群體的搜索演算法進行優化
- 設計科學實驗，通過使其真正隨機來產生更有意義的結果
- 實現神經網絡和隨機森林等機器學習演算法
- 使用馬爾可夫鏈蒙特卡羅方法從複雜分佈中進行抽樣
- 在音頻文件和圖像中隱藏資訊，生成藝術和創作音樂
- 從僅有的隨機採樣數據中重建原始信號和圖像

全書中的科學趣聞和程式碼示例說明了隨機性在優化、機器學習和音頻信號等領域的應用。章末練習鼓勵進一步探索。無論你是程式設計師、科學家、工程師、數學家還是藝術家，你都會發現《隨機性的藝術》是你發現應用隨機性的隱藏力量以及它如何改變你解決問題方法的通行證，從技術到藝術。

Ronald T. Kneusel is a computer scientist, an expert in machine learning, and a lover of fine craft beers. Kneusel has been working with machine learning in industry since 2003 and completed a PhD in machine learning from the University of Colorado, Boulder, in 2016. He's the author of four other books with No Starch Press: How AI Works (2023), Strange Code (2022), Practical Deep Learning (2021), and Math for Deep Learning (2021).

Ronald T. Kneusel 是一位電腦科學家，機器學習專家，也是一位喜愛精緻手工啤酒的愛好者。Kneusel 自 2003 年以來一直在工業界從事機器學習的工作，並於 2016 年在科羅拉多大學波德分校完成了機器學習的博士學位。他是 No Starch Press 出版的其他四本書的作者: 《How AI Works》(2023)、《Strange Code》(2022)、《Practical Deep Learning》(2021) 和 《Math for Deep Learning》(2021)。