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	<title>Moataz Gaber &#8211; Noise</title>
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		<title>Field Notes: Comparing Algorithm Performance Using MLOps and the AWS Cloud Development Kit</title>
		<link>https://noise.getoto.net/2021/01/06/field-notes-comparing-algorithm-performance-using-mlops-and-the-aws-cloud-development-kit/</link>
		
		<dc:creator><![CDATA[Moataz Gaber]]></dc:creator>
		<pubDate>Wed, 06 Jan 2021 18:28:56 +0000</pubDate>
				<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Cloud Development Kit]]></category>
		<category><![CDATA[Field Notes]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Comparing machine learning algorithm performance is fundamental for machine learning practitioners, and data scientists. The goal is to evaluate the appropriate algorithm to implement for a known business problem. Machine learning performance is often correlated to the usefulness of the model deployed. Improving the performance of the model typically results in an increased accuracy of [&#8230;]]]></description>
		
		
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