<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Introduction on Chen Kai Blog</title><link>https://www.chenk.top/en/tags/introduction/</link><description>Recent content in Introduction on Chen Kai Blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 01 Dec 2025 09:00:00 +0000</lastBuildDate><atom:link href="https://www.chenk.top/en/tags/introduction/index.xml" rel="self" type="application/rss+xml"/><item><title>Recommendation Systems (1): Fundamentals and Core Concepts</title><link>https://www.chenk.top/en/recommendation-systems/01-fundamentals/</link><pubDate>Mon, 01 Dec 2025 09:00:00 +0000</pubDate><guid>https://www.chenk.top/en/recommendation-systems/01-fundamentals/</guid><description>&lt;p>Open Netflix and the homepage somehow knows you. Scroll TikTok and the next video is the one you didn&amp;rsquo;t realise you wanted. Drop into Spotify on a Monday morning and &lt;em>Discover Weekly&lt;/em> serves up thirty songs you&amp;rsquo;ve never heard of, and you save half of them.&lt;/p>
&lt;p>None of this is magic. It is one of the most commercially successful applications of machine learning, quietly running behind almost every consumer product you use: the &lt;strong>recommendation system&lt;/strong>.&lt;/p></description></item></channel></rss>