I want to create a complete End to End ML system, where I train several models and deploy the best.
Currently, I have an End-to-End System where I used The Azure ML SDK with Azure DevOps.
Here all the DevOps Training jobs are run using the Azure ML SDK. They are launched within Azure DevOps.
Now, I want to use the Azure ML Pipeline for Model Training and Registering instead of using the Azure ML SDK. Azure ML Training Pipeline.
How can I use the models trained in the Azure ML Studio Pipelines and deploy it using Azure DevOps?
Currently, I pass the metadata generated from the Azure Training jobs to the CD pipeline as artifacts, and then from there, I can deploy the best model.
Now with Azure Pipeline, how can that be done?