Deploy and tune models in Azure Databricks

Rating & reviews (0 reviews)
Study notes

Model Deployment
Process by which you integrate your trained machine learning models into a production environment such that your business or end-user applications can use the model predictions to make decisions or gain insights into your data.
The most common way you deploy a model using Azure Machine Learning from Azure Databricks, is to deploy the model as a real-time inferencing service

Deploy Azure Databricks models in Azure Machine Learning - Training | Microsoft Learn
Tune hyperparameters with Azure Databricks - Training | Microsoft Learn
Distributed deep learning with Horovod and Azure Databricks - Training | Microsoft Learn