Design considerations - Predictive Segmentation Using Amazon Pinpoint and Amazon SageMaker

Design considerations

Customization

By default, Predictive Segmentation Using Amazon Pinpoint and Amazon SageMaker uses a simple, example dataset to train the machine learning (ML) model. You can customize the solution to use your own dataset. To train the model on your own dataset, you must modify the included notebook to point the model to your dataset. You must also create your own Amazon Athena query, and modify the solution’s AWS Lambda function to point to that query. For more information, refer to Using your own dataset.

Regional deployment

This solution uses Amazon Pinpoint, which is currently available in specific AWS Regions only. Therefore, you must launch this solution in a Region where Amazon Pinpoint is available. For the most current service availability by Region, refer to the AWS Regional Services List.