<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Regularization &#8211; Howard Nguyen</title>
	<atom:link href="https://howardnguyen.com/category/regularization/feed/" rel="self" type="application/rss+xml" />
	<link>https://howardnguyen.com</link>
	<description>Ph.D. in Data Science</description>
	<lastBuildDate>Sun, 30 Jun 2024 18:06:52 +0000</lastBuildDate>
	<language>en</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=6.8.3</generator>

<image>
	<url>https://howardnguyen.com/wp-content/uploads/2023/05/H-icon3-36x36.png</url>
	<title>Regularization &#8211; Howard Nguyen</title>
	<link>https://howardnguyen.com</link>
	<width>32</width>
	<height>32</height>
</image> 
	<item>
		<title>What is regularization and why it is important?</title>
		<link>https://howardnguyen.com/what-is-regularization-and-why-it-is-important/</link>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Sun, 30 Jun 2024 17:50:21 +0000</pubDate>
				<category><![CDATA[Data Analysis]]></category>
		<category><![CDATA[Data Science]]></category>
		<category><![CDATA[EDA]]></category>
		<category><![CDATA[Exploratory Data Analysis]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Regularization]]></category>
		<category><![CDATA[Machine Learning Model]]></category>
		<guid isPermaLink="false">https://howardnguyen.com/?p=1134</guid>

					<description><![CDATA[]]></description>
										<content:encoded><![CDATA[<p>Why it is important? Regularization is a technique used in machine learning and statistics to prevent overfitting, which occurs when a model learns the noise in the training data instead of the actual underlying patterns. Regularization adds a penalty to the model&rsquo;s complexity, discouraging it from fitting too closely to the training data. This helps improve the model&rsquo;s generalization to new&#8230;</p>
<p><a href="https://howardnguyen.com/what-is-regularization-and-why-it-is-important/" rel="nofollow">Source</a></p>]]></content:encoded>
					
		
		
			</item>
	</channel>
</rss>
