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Patrycja-J authored Aug 14, 2023
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# Neptune + scikit-learn integration

Experiment tracking, model registry, data versioning, and live model monitoring for scikit-learn (sklearn) trained models.
Experiment tracking for scikit-learn (sklearn) trained models.

## What will you get with this integration?

* Log, display, organize, and compare ML experiments in a single place
* Version, store, manage, and query trained models, and model building metadata
* Record and monitor model training, evaluation, or production runs live
* Log, organize, visualize, and compare ML experiments in a single place
* Monitor model training live
* Version and query production-ready models and associated metadata (e.g., datasets)
* Collaborate with the team and across the organization

## What will be logged to Neptune?

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* metadata including git summary info,
* [other metadata](https://docs.neptune.ai/logging/what_you_can_log)

![image](https://user-images.githubusercontent.com/97611089/160642485-afca99da-9f7b-4d80-b0be-810c9d5770e5.png)
*Confusion matrix logged to Neptune*
![image](https://docs.neptune.ai/img/app/integrations/scikit-learn.png)

## Resources

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