User guide#

Below is a gallery of narrated notebook examples on how and why to use skore. They serve as our user guide.

Getting started#

We recommend first having a look at the Quick start page. Then, the Skore: getting started provides an overall and gentle introduction to skore.

Quick start

Quick start

Skore: getting started

Skore: getting started

Tracking items

Tracking items

Working with projects

Working with projects

End-to-end data science use cases#

These examples show skore in action on real use cases. We aimed at showing skore’s ability to:

  • be compatible with scikit-learn

  • reduce boilerplate code for some standard de facto data science analysis

  • speed-up exploration by optimizing some internal computation

Simplified experiment reporting

Simplified experiment reporting

Model evaluation#

These examples illustrate how skore can help data scientists to improve their machine learning modelling thanks to diagnostics.

Cross-validation

Cross-validation

Get insights from any scikit-learn estimator

Get insights from any scikit-learn estimator

Train-test split

Train-test split

Technical details#

These examples shows some technical details at the core of skore to better understand some of the mechanics under the hood.

Cache mechanism

Cache mechanism

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