Скачать или смотреть Buzz or Noise? Clustering with DBSCAN

Bee Swarms & Noisy Tins — DBSCAN Explained

What if your data grouped itself naturally, like bees forming swarms? 🌳 In this episode, Bonnie & Clyde the cats explore DBSCAN, a clustering algorithm that finds dense groups on its own — and marks the loners as noise.

You’ll learn:
How DBSCAN works to discover natural clusters 🐝
Why clustering doesn’t need labels 📦
The advantage of not picking the number of clusters upfront 🔢
Why most tins in our dataset looked noisy ⚠️
When clustering works best (only if your data has a clear structure)

From swarms to loners, DBSCAN shows us how to handle messy, real-world data — no guessing required.

📘 Dive deeper into the world of AI with Machine Learning: for Humans on Cats — now on Amazon!
👉 https://www.amazon.com/dp/B0CW9SFYXF

💻 Try the code yourself & follow along with tutorials at:
👉 https://katerynakononova.github.io/me...
It’s purr-fectly beginner-friendly. 😺🚀

Don’t forget to like, subscribe, and share with your fellow curious cats! 🐾
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