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	<title>Wei Teh &#8211; Noise</title>
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		<title>Field Notes: Build a Cross-Validation Machine Learning Model Pipeline at Scale with Amazon SageMaker</title>
		<link>https://noise.getoto.net/2021/10/06/field-notes-build-a-cross-validation-machine-learning-model-pipeline-at-scale-with-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Wei Teh]]></dc:creator>
		<pubDate>Wed, 06 Oct 2021 13:40:59 +0000</pubDate>
				<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[Field Notes]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[When building a machine learning algorithm, such as a regression or classification algorithm, a common goal is to produce a generalized model. This is so that it performs well on new data that the model has not seen before. Overfitting and underfitting are two fundamental causes of poor performance for machine learning models. A model […]]]></description>
		
		
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