<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Svm on DATATWEETS</title><link>https://datatweets.com/tags/svm/</link><description>Recent content in Svm on DATATWEETS</description><generator>Hugo</generator><language>en</language><copyright>Copyright (c) 2026 Datatweets</copyright><lastBuildDate>Sat, 11 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://datatweets.com/tags/svm/index.xml" rel="self" type="application/rss+xml"/><item><title>Support Vector Machines in Python: Margins, Kernels, and C</title><link>https://datatweets.com/tutorials/support-vector-machines-in-python/</link><pubDate>Sat, 11 Jul 2026 00:00:00 +0000</pubDate><guid>https://datatweets.com/tutorials/support-vector-machines-in-python/</guid><description>A focused, code-verified introduction to Support Vector Machines: why SVC looks for the widest possible margin instead of just any separating line, what the fitted support vectors actually are, how the C parameter trades margin width for misclassification tolerance, and how the kernel trick handles data a straight line can&amp;rsquo;t separate.</description></item></channel></rss>