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		<title>deep learning: Linear Autoencoder with Keras</title>
		<link>https://petaminds.com/deep-learning-linear-autoencoder-with-keras/</link>
					<comments>https://petaminds.com/deep-learning-linear-autoencoder-with-keras/#respond</comments>
		
		<dc:creator><![CDATA[Tung Nguyen]]></dc:creator>
		<pubDate>Mon, 09 Dec 2019 02:22:01 +0000</pubDate>
				<category><![CDATA[data science]]></category>
		<category><![CDATA[Project]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[visualization]]></category>
		<category><![CDATA[auto]]></category>
		<category><![CDATA[decoder]]></category>
		<category><![CDATA[dimension]]></category>
		<category><![CDATA[encoder]]></category>
		<category><![CDATA[keras]]></category>
		<category><![CDATA[reduction]]></category>
		<category><![CDATA[tensorflow]]></category>
		<guid isPermaLink="false">https://petaminds.com/?p=2027</guid>

					<description><![CDATA[<p>This post introduces using linear autoencoder for dimensionality reduction using TensorFlow and Keras. What is a linear autoencoder An autoencoder is a type of artificial neural network used to learn efficient data codings in an unsupervised manner. The aim of an autoencoder is to learn a representation (encoding) for a set of data, typically for dimensionality reduction, by training the network to ignore signal “noise”. Autoencoders consists [&#8230;]</p>
<p>The post <a href="https://petaminds.com/deep-learning-linear-autoencoder-with-keras/">deep learning: Linear Autoencoder with Keras</a> appeared first on <a href="https://petaminds.com">Petamind</a>.</p>
]]></description>
		
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