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๐Ÿ“š Jupyter Notebooks extension for versioning, managing and sharing notebook checkpoints in your machine learning and data science projects.

Home Page: https://docs.neptune.ai/tools/jupyter/overview/

License: Apache License 2.0

JavaScript 4.96% Makefile 0.11% Python 48.12% TypeScript 40.99% Shell 0.10% Less 5.73%
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neptune-notebooks's Introduction

Neptune-Jupyter integration

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.

What will you get with this integration?

  • Log and display notebook checkpoints either manually or automatically during model training
  • Connect notebook checkpoints with model training runs in Neptune
  • Organize checkpoints with names and descriptions
  • Browse checkpoints history across all notebooks in the project
  • Compare Notebooks side-by-side, with diffs for source, markdown, output, and execution count cells
  • Share Notebook checkpoints or diffs with persistent links
  • Download Notebook checkpoints directly from Neptune or Jupyter

Jupyter Notebook rendered in Neptune

Resources

Setup

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.

  1. To connect with Neptune, click the Neptune Configure button.
  2. Enter your Neptune credentials.
  3. To register the notebook in Neptune, click Upload.

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.

Usage

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.

Support

If you got stuck or simply want to talk to us, here are your options:

  • Check our FAQ page
  • You can submit bug reports, feature requests, or contributions directly to this repository
  • Chat! When in the Neptune application click on the blue message icon in the bottom-right corner and send a message. A real person will talk to you ASAP (typically very ASAP)
  • You can just shoot us an email at [email protected]

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