Personalizer - Building the Personalizer Loop and Testing Model

Learn to build a recommendation system using the Azure Personalizer SDK for Python.

To recap, in the previous lesson, we’ve prepared the dataset, created the action items that we want to be ranked, created a method to get the user profile information. In this lesson, we’ll perform the remaining step to build the personalizer loop and implement the Rank and Reward API calls.

Updating the configuration setting

Before moving on, we need to make a configuration setting for the personalizer service in the Azure Portal to make the updates to the personalizer model at every 30 second. You can refer to the illustration below:

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