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<oembed><version>1.0</version><provider_name>Glosarix</provider_name><provider_url>https://glosarix.com/en/</provider_url><author_name>Team Glosarix</author_name><author_url>https://glosarix.com/en/author/adm_glosarix/</author_url><title>The Models tuning - Glosarix</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="MKtcKA6Izk"&gt;&lt;a href="https://glosarix.com/en/glossary/the-models-tuning-en/"&gt;The Models tuning&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://glosarix.com/en/glossary/the-models-tuning-en/embed/#?secret=MKtcKA6Izk" width="600" height="338" title="&#x201C;The Models tuning&#x201D; &#x2014; Glosarix" data-secret="MKtcKA6Izk" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>Description: Model tuning is the process of refining a model to improve its accuracy and effectiveness. In the context of data science, this process involves selecting parameters and optimizing algorithms so that the model fits the available data better. This can include techniques such as cross-validation, where the dataset is divided into several parts to [&hellip;]</description></oembed>
