Working with JupyterLab and Jupyter Notebook#

Note

If you just want to see how to use Neptune in a Jupyter notebook, see for example Working with Colab and Adding Neptune to your code.

JupyterLab and Jupyter Notebook are popular IDEs used by data scientists for task such as data exploration, model training, error analysis, and reporting.

With the Neptune–Jupyter extension, you can snapshot your notebook code and have more options for notebook versioning and comparison in Neptune.

With the Neptune–Jupyter integration, you can:

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.

See example notebook in Neptune