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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>Neural Network Hyperparameters - Glosarix</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="2KGNEK58Si"&gt;&lt;a href="https://glosarix.com/en/glossary/neural-network-hyperparameters-en/"&gt;Neural Network Hyperparameters&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://glosarix.com/en/glossary/neural-network-hyperparameters-en/embed/#?secret=2KGNEK58Si" width="600" height="338" title="&#x201C;Neural Network Hyperparameters&#x201D; &#x2014; Glosarix" data-secret="2KGNEK58Si" 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: Neural network hyperparameters are the parameters that are set before the training process begins. These parameters are crucial for the model&#x2019;s performance, as they determine the structure and behavior of the network. Unlike model parameters, which are adjusted during training through optimization algorithms, hyperparameters must be defined manually and can include elements such as [&hellip;]</description></oembed>
