📚 Jupyter Notebooks extension for versioning, managing and sharing notebook checkpoints in your machine learning and data science projects.
Neptune is a lightweight experiment tracker that offers a single place to track, compare, store, and collaborate on experiments and models.
The Neptune-Jupyter extension lets you version, manage, and share notebook checkpoints in your projects.
Note: The extension currently works for JupyterLab <4.0
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Install the extension:
pip install neptune-notebooks
Enable the extension for Jupyter:
jupyter nbextension enable --py neptune-notebooks
In your Jupyter Notebook environment, some Neptune items appear in your toolbar.
This uploads a first checkpoint of the notebook. Every time you start a Neptune run in the notebook, a checkpoint is uploaded automatically.
For detailed instructions, see the Neptune documentation.
In a notebook cell, import neptune and start a run:
import neptune
run = neptune.init_run()
Log model-building metadata that you care about:
run["f1_score"] = 0.66
For what else you can track, see What you can log and display in the Neptune docs.
When you're done with the logging, stop the run:
run.stop()
You can view the notebook snapshot in the run's Source code dashboard or the project's Notebooks section.
If you got stuck or simply want to talk to us, here are your options: