<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>K-Means on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/k-means/</link><description>Recent content in K-Means on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sun, 18 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/k-means/index.xml" rel="self" type="application/rss+xml"/><item><title>Chapter 8: Unsupervised Learning: Finding Hidden Patterns</title><link>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/unsupervised-learning-intro/</link><pubDate>Sun, 18 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/unsupervised-learning-intro/</guid><description>&lt;h2 id="introduction-the-detective-of-data"&gt;Introduction: The Detective of Data&lt;/h2&gt;
&lt;p&gt;Welcome back, future AI wizard! So far in our journey, we&amp;rsquo;ve explored the exciting world of Supervised Learning. Remember how we trained models with labeled data, like teaching a child to identify cats by showing them pictures &lt;em&gt;labeled&lt;/em&gt; &amp;ldquo;cat&amp;rdquo;? We had a &amp;ldquo;teacher&amp;rdquo; telling the model what the correct answer was.&lt;/p&gt;
&lt;p&gt;But what if there&amp;rsquo;s no teacher? What if you have a huge pile of information and no one tells you what&amp;rsquo;s what? This is where a truly fascinating side of Machine Learning comes in: &lt;strong&gt;Unsupervised Learning&lt;/strong&gt;.&lt;/p&gt;</description></item></channel></rss>