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Intro to Kedro-Neptune plugin
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Basic example
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Advanced example
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Exploring predictions
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Grouping runs
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Converting nodes
Important: This video was created in October 2021. For the most up-to-date code examples, please refer to the Neptune-Kedro integration docs.
What will you get with the Neptune-Kedro integration?
Kedro is a popular open-source project that helps standardize ML workflows. It gives you a clean and powerful pipeline abstraction where you put all your ML code logic.
Kedro-Neptune plugin lets you have all the benefits of a nicely organized kedro pipeline with a powerful user interface built for ML metadata management that lets you:
- Browse, filter, and sort your model training runs
- Compare nodes and pipelines on metrics, visual node outputs
- Display all pipeline metadata including learning curves for metrics, plots, images, rich media or interactive visualizations from Plotly, Altair, or Bokeh
- And do whatever else you would expect from a modern ML metadata store
neptune.ai is an MLOps stack component for experiment tracking. So we’re constantly working on making it easy to integrate with other parts of the workflow.
It is already integrated with 25+ tools and libraries, and the list is growing. You can check our roadmap to see what’s currently under development.
Other useful resources
More about How to Organize Kedro Pipelines: Kedro + neptune.ai Integration
See also
What is a Project in Neptune?
See also
Model Training: Detectron2 + neptune.ai Integration [Example]
See also
Model Training: Prophet + neptune.ai Integration [Example]
See also
Create AzureML Pipeline – Workshop with Aurimas Griciūnas
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