In this video, we show how to keep track of your model-training metadata when using scikit-learn. Prince Canuma explains:
- How to use the Neptune-scikit-learn (sklearn) integration,
- How to log your sklearn training metadata to Neptune (including regressor parameters, pickled model, test predictions, test scores, and more),
- How to analyze the data in the Neptune app,
- And more.
Important: This video was created in December 2021. For the most up-to-date tutorials and examples, please refer to the Neptune-scikit-learn integration docs.
We are 100% focused on ML metadata management, but we’re making sure that it’s easy to integrate Neptune with other components of the ML stack.
Other useful resources
See a Scikit-learn example project in the Neptune app (no registration needed).