Use Case Documentation
Model Drift and Monitoring

Choose this use-case if you wish to monitor the status of your deployed machine learning model over time. Given the original training dataset used and a dataset containing new data the model is making predictions on, you can track your model's accuracy over time.

Dataset and Feature Group Requirements

This section specifies the Datasets / Feature Groups requirements to successfully train a Model Drift and Monitoring model. Feature requirements include recommendations on additional datasets that might enhance model performance.

Training Models - Training Options and Metrics

This section describes all the available model training options that can be used to create a Model Drift and Monitoring model. You can utilize the metric explanations to better understand how they measure the performance of the model you trained.

Prediction API

This section discusses the prediction API method so that you could properly generate predictions from the model you deployed.