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		<title>One-hot encoding quick note</title>
		<link>https://petaminds.com/one-hot-encoding-quick-note/</link>
					<comments>https://petaminds.com/one-hot-encoding-quick-note/#comments</comments>
		
		<dc:creator><![CDATA[Tung Nguyen]]></dc:creator>
		<pubDate>Fri, 01 Feb 2019 11:43:44 +0000</pubDate>
				<category><![CDATA[data science]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[keras]]></category>
		<category><![CDATA[sklearn]]></category>
		<guid isPermaLink="false">https://petaminds.com/?p=803</guid>

					<description><![CDATA[<p>Quickly grasp the concept of one-hot encoding by simple data and coding. Categorical VS Numerical data Categorical data are variables that contain label values. For example, A “colour” variable can have values &#8220;red&#8220;, &#8220;green&#8221; and &#8220;blue&#8220;. Here, &#8220;red&#8221;, &#8220;green&#8221;, &#8220;blue&#8221; are labels represented by strings. Numerical data are variables that contain numeric values. For example, [&#8230;]</p>
<p>The post <a href="https://petaminds.com/one-hot-encoding-quick-note/">One-hot encoding quick note</a> appeared first on <a href="https://petaminds.com">Petamind</a>.</p>
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