<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Prediction on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/prediction/</link><description>Recent content in Prediction 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/prediction/index.xml" rel="self" type="application/rss+xml"/><item><title>Chapter 4: How Machines Learn: Training and Prediction Explained</title><link>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/training-prediction-explained/</link><pubDate>Sun, 18 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/training-prediction-explained/</guid><description>&lt;h2 id="chapter-4-how-machines-learn-training-and-prediction-explained"&gt;Chapter 4: How Machines Learn: Training and Prediction Explained&lt;/h2&gt;
&lt;p&gt;Welcome back, future AI explorer! In our last chapter, we started to understand what an AI &amp;ldquo;model&amp;rdquo; is – essentially, a smart recipe or a set of rules that can make decisions or predictions. But how does this &amp;ldquo;recipe&amp;rdquo; get written? How does a model become smart? That&amp;rsquo;s exactly what we&amp;rsquo;ll uncover in this chapter: the fascinating processes of &lt;strong&gt;training&lt;/strong&gt; and &lt;strong&gt;prediction&lt;/strong&gt;.&lt;/p&gt;</description></item><item><title>Prediction: AI&amp;#39;s Best Guess</title><link>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/ai-predictions-explained/</link><pubDate>Sun, 18 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/ai-predictions-explained/</guid><description>&lt;h2 id="welcome-to-chapter-8-prediction-ais-best-guess"&gt;Welcome to Chapter 8: Prediction: AI&amp;rsquo;s Best Guess!&lt;/h2&gt;
&lt;p&gt;Hello, future AI explorer! You&amp;rsquo;re doing an amazing job on this journey. So far, we&amp;rsquo;ve talked about what AI and Machine Learning are, how they learn from &lt;strong&gt;data&lt;/strong&gt;, build &lt;strong&gt;models&lt;/strong&gt;, and go through a &lt;strong&gt;training&lt;/strong&gt; process. Remember how we compared training to teaching a child or baking a cake?&lt;/p&gt;
&lt;p&gt;Today, we&amp;rsquo;re going to dive into one of the most exciting parts of AI: &lt;strong&gt;prediction&lt;/strong&gt;. This is where all that learning and training pays off! Think of it like a friendly fortune teller, but instead of magic, our AI uses patterns it learned from tons of information to make its best guess about what might happen next, or what something might be.&lt;/p&gt;</description></item></channel></rss>