<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Data Science on Prahyat Puangjaktha | Hub</title><link>https://prayat-pu.github.io/py-website/tags/data-science/</link><description>Recent content in Data Science on Prahyat Puangjaktha | Hub</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://prayat-pu.github.io/py-website/tags/data-science/index.xml" rel="self" type="application/rss+xml"/><item><title>Data Science Cheat Sheet</title><link>https://prayat-pu.github.io/py-website/resources/ds-cheat-sheet/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://prayat-pu.github.io/py-website/resources/ds-cheat-sheet/</guid><description>&lt;p&gt;A quick reference guide for essential Data Science libraries:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Pandas:&lt;/strong&gt; Data manipulation and analysis.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Numpy:&lt;/strong&gt; Numerical computing.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Scikit-Learn:&lt;/strong&gt; Machine learning algorithms.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Matplotlib:&lt;/strong&gt; Data visualization.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;a href="https://github.com/prayat-pu"&gt;Download the Full Cheat Sheet&lt;/a&gt;&lt;/p&gt;</description></item></channel></rss>