Add AutoML functionality with Amazon SageMaker Autopilot across accounts

AutoML is a powerful capability, provided by Amazon SageMaker Autopilot, that allows non-experts to create machine learning (ML) models to invoke in their applications. The problem that we want to solve arises when, due to governance constraints, Amazon SageMaker resources can't be deployed in the same AWS account where they are used. This post walks through an implementation using the SageMaker Python SDK. It's divided into two sections: The solution described in this post is provided in the Jupyter notebook available in this GitHub repository. For a full explanation of Autopilot, you can refer to the examples available in GitHub, particularly Top Candidates Customer Churn Prediction with Amazon SageMaker Autopilot and Batch Transform (Python SDK).