In a scenario where you are working on a machine learning project that requires the deployment of trained models for real-time predictions, explain how Databricks can help in deploying and managing the models.

Simulated

Databricks can only be used for training machine learning models, and model deployment is not supported.

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Databricks can be used for deploying machine learning models, but managing the models and handling real-time predictions requires additional tools and infrastructure.

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Databricks provides built-in support for deploying machine learning models as REST APIs, making it easy to integrate with applications for real-time predictions. It also provides tools for managing the models and handling scalability and performance.

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Databricks can be used for deploying machine learning models, but it does not provide any support for real-time predictions or managing the models.

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Databricks Certified Machine Learning - Associate

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In a scenario where you are working on a machine learning project that requires the deployment of trained models for real-time predictions, explain how Databricks can help in deploying and managing the models.