How to Log and Analyze Model Training Metadata

1 min
Kamil Kaczmarek
21st April, 2022

What will you learn?
How you can log and inspect all the metadata generated during various model training sessions in Neptune.

  • 00:12

    How to use Neptune integrations and what do you get by default?

  • 01:59

    Analyzing the logged metrics

  • 03:18

    What else can I log to Neptune using the Python client?

  • 04:08

    You can log the metadata in a hierarchical structure using the namespaces

  • 06:00

    You can also log the images and files to Neptune

  • 07:06

    Exploring all the logged metadata in the Neptune UI

  • 07:33

    Visualizing the model parameters, summary and checkpoints in the Neptune UI

  • 07:57

    You can optionally associate the source code with the Neptune run

  • 08:45

    Neptune automatically tracks your Git info

  • 09:14

    How can I share a particular view inside my run with a team member?

  • 09:45

    Can I log the tabular data (i.e. pandas dataframes)?

  • 10:18

    You can associate some additional information to your images (i.e. class probability)

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

Other useful resources

Check the docs on what you can log and display

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