This article https://azure.microsoft.com/en-gb/blog/experimentation-using-azure-machine-learning/ from @danielsc can be used as a base
I'm working on AML + hyperdrive for wide-deep, excluding auto-ml (don't think we --recommender-- can use automl). Basically I have two notebooks around 75% ready, one for wide-deep and the other one for aml+hyperdrive for wide-deep tuning
FYI team I am also working on the Spark-based hyper tune which extends my current illustrative notebook here. Idea is to show how pipeline feature of AML can be used for tuning Spark models on Azure Databricks.
closing this since it has been solved on #448 and on #546
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I'm working on AML + hyperdrive for wide-deep, excluding auto-ml (don't think we --recommender-- can use automl). Basically I have two notebooks around 75% ready, one for wide-deep and the other one for aml+hyperdrive for wide-deep tuning