How to Track XGBoost Experiments and Data Versions

1 min
Dominika Kozub
14th December, 2022

What will you learn?

How you can log XGBoost experiments and track multiple data versions locally or in the cloud using

  • 00:11

    Creating a Neptune run

  • 01:47

    Tracking and versioning datasets stored in the S3

  • 02:35

    How does versioning work in Neptune?

  • 03:06

    Will Neptune store a dataset?

  • 03:15

    How can I log in a synchronous way?

  • 03:43

    How can I log and visualize samples of a dataset?

  • 05:02

    Is the data sample uploaded to the Neptune servers?

  • 05:24

    What are the namespaces?

  • 05:42

    How to use Neptune callback to track the XGBboost model training?

  • 06:30

    What are the benefits of using a Neptune integration?

  • 07:07

    Can I fetch metadata I logged to a Neptune run?

  • 08:14

    How to log test metrics?

  • 09:00

    Does Neptune store my trained models?

Important: This video was created in December 2022. For the most up-to-date code examples, please refer to the Neptune docs

Other useful resources

See the docs on versioning datasets in runs.

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