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How can MLflow, integrated within Databricks on Azure, be utilized for deploying models in a production environment? (Choose Three Options)
A
Exporting the model to a Docker container for deployment on Kubernetes.
B
Manual deployment by downloading the model artifacts and using Azure Functions.
C
Direct deployment to Azure Machine Learning as a web service.
D
Uploading the model binaries directly to Azure SQL Database for real-time predictions.
