Build dashboards with the MLflow Search API

You can pull aggregate metrics on your MLflow runs using the mlflow.search_runs API and display them in a dashboard. Regularly such reviewing metrics can provide insight into your progress and productivity. For example, you can track improvement of a goal metric like revenue or accuracy over time, across many runs and/or experiments.

This notebook demonstrates how to build the following custom dashboard using the mlflow.search_runs API:

You can either run the notebook on your own experiments or against autogenerated mock experiment data.

Dashboard comparing MLflow runs notebook

Open notebook in new tab Copy link for import