Hello, I have been using kedro-azureml specifically for online inference and it has been really nice. So first let me say thank you for all that you do.

For my question, I am having a hard time figuring out how to use kedro-azureml to create an azureml pipeline that is used for batch predictions.

What I am trying to achieve are the following:

• Read data directly from Azure DataLake something like "adl://path"
• Specify the location of the output to either adl or to blob storage
• use azureml to schedule this job to run on scheduler

My specific use case is that I always need to retrain the model (A survival model written in PYMC) before producing predictions so ideally I just want a kedro pipeline to be converted to an azureml pipeline where I can specify the input and output.

Are these functions already something that are available in kedro-azureml?