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Tracking models end-to-end#

To track a model across all stages of its lifecycle, you can use Neptune for the following:

  • Logging model and run metadata to a central project
  • Comparing runs to select the best performing model
  • Monitoring a model once in production

To demonstrate this, we provide an example notebook and script.


The example uses Optuna hyperparameter-optimization to simulate the training and evaluating of multiple scikit-learn models, and Evidently to monitor models in production.

However, you can use any library and framework of your choice.

The script can be used as a template to design an automated end-to-end pipeline that covers the entire lifecycle of a model without needing any manual intervention.

See in Neptune  See script on GitHub 

To download the notebooks and scripts of this example, visit the Neptune examples repo .