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		<title>Fast uniform negative sampling for rating matrix</title>
		<link>https://petaminds.com/fast-uniform-negative-sampling-for-rating-matrix/</link>
					<comments>https://petaminds.com/fast-uniform-negative-sampling-for-rating-matrix/#comments</comments>
		
		<dc:creator><![CDATA[Tung Nguyen]]></dc:creator>
		<pubDate>Fri, 21 Feb 2020 10:07:13 +0000</pubDate>
				<category><![CDATA[data science]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[matrix]]></category>
		<category><![CDATA[negative sampling]]></category>
		<category><![CDATA[numpy]]></category>
		<category><![CDATA[python]]></category>
		<category><![CDATA[rating]]></category>
		<category><![CDATA[scipy]]></category>
		<guid isPermaLink="false">https://petaminds.com/?p=2250</guid>

					<description><![CDATA[<p>Sometimes, we want to reduce the training time by using a subset of a very large dataset while the negative samples outnumbers the positive ones, e.g. word embedding. Another situation when we deal with implicit data. In this case, we may need to populate new data for negative values. This post demonstrates how to generate [&#8230;]</p>
<p>The post <a href="https://petaminds.com/fast-uniform-negative-sampling-for-rating-matrix/">Fast uniform negative sampling for rating matrix</a> appeared first on <a href="https://petaminds.com">Petamind</a>.</p>
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		<title>Dimension, Dimension, Dimension &#8211; Reshape your data</title>
		<link>https://petaminds.com/dimension-dimension-dimension-reshape-your-data/</link>
					<comments>https://petaminds.com/dimension-dimension-dimension-reshape-your-data/#respond</comments>
		
		<dc:creator><![CDATA[Tung Nguyen]]></dc:creator>
		<pubDate>Mon, 28 Oct 2019 21:45:59 +0000</pubDate>
				<category><![CDATA[data science]]></category>
		<category><![CDATA[Project]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[dimension]]></category>
		<category><![CDATA[numpy]]></category>
		<category><![CDATA[pandas]]></category>
		<category><![CDATA[reshape]]></category>
		<category><![CDATA[tensorflow]]></category>
		<category><![CDATA[tf]]></category>
		<guid isPermaLink="false">https://petaminds.com/?p=1553</guid>

					<description><![CDATA[<p>The most basic yet important thing when working with data array is its dimensions. This article will cover several data shapes and reshaping techniques. Why need reshaping data Imagine that you are starving and suddenly given a piece of delicious food. You may try to put it all in your mouth (Fig 1a) and find [&#8230;]</p>
<p>The post <a href="https://petaminds.com/dimension-dimension-dimension-reshape-your-data/">Dimension, Dimension, Dimension &#8211; Reshape your data</a> appeared first on <a href="https://petaminds.com">Petamind</a>.</p>
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