ujjwalkarn/programming-collective-intelligence-code

This repository contains code examples from the O'Reilly book "Programming Collective Intelligence." The book teaches you how to build systems that learn patterns from groups of people and make smarter decisions based on that collective behavior. In plain terms, the code demonstrates techniques for things like recommendation engines (suggesting products based on what similar customers bought), clustering (grouping things together automatically), and ranking (figuring out what matters most). These are the kinds of algorithms that power features like "customers who bought this also bought that" on shopping sites, or how streaming services suggest shows you might enjoy. The examples are written in Python, a beginner-friendly programming language. Each script tackles a different problem, like predicting preferences or finding patterns in data, so you can learn by reading through working code and experimenting with it yourself. The repository doesn't include the full book text, just the runnable code samples that accompany each chapter. This would be useful if you're learning how recommendation systems work, building your first machine learning project, or trying to understand the foundations of how AI learns from human behavior. Rather than starting from scratch, you get real code you can run, modify, and learn from. It's the kind of resource someone might use when taking the book's lessons and wanting to tinker with the actual implementation before applying those ideas to their own project.