Electron microscopy
 
Comparisons among Manual Search, Vertex Vizier,
AutoML and Early stopping on google cloud

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Table 3751. Comparisons among Manual Search, Vertex Vizier, AutoML and Early stopping on google cloud.

  Manual Search Vertex Vizier AutoML Early stopping
Definition   Vertex Vizier is a hyperparameter tuning service on Google Cloud that automates the tuning process. Google Cloud AutoML is a suite of machine learning products that automates the process of building and deploying machine learning models. Early stopping is a technique used during the training of machine learning models to halt training once a certain criteria (e.g., validation loss) stops improving.
Advantages        Full control over the hyperparameter tuning process.
       Can leverage domain knowledge and intuition.
       Automated and scalable hyperparameter optimization.
       Efficient exploration of the hyperparameter space.
       Integrates with Google Cloud AI Platform.
       Requires minimal machine learning expertise.
       Automates model selection, hyperparameter tuning, and deployment.
       Handles various aspects of the machine learning pipeline.
       Helps prevent overfitting and improves generalization.
       Saves training time and resources.
Diadvantages        Time-consuming and resource-intensive.
       Prone to human bias and errors.
       May not be optimal for large-scale parameter spaces.
       Requires a clear definition of the objective metric.
       Limited to the algorithms and configurations supported by Vizier.
       Limited customization compared to manual tuning.
       May not be suitable for highly specialized tasks.
       Requires careful monitoring and tuning of the stopping criteria.
       May stop training prematurely if not configured properly.

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