Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/probabl-ai/skore

The scikit-learn Modeling Companion
https://github.com/probabl-ai/skore

data-analysis data-science data-visualization machine-learning python scikit-learn workflow

Last synced: about 12 hours ago
JSON representation

The scikit-learn Modeling Companion

Awesome Lists containing this project

README 

        



  

    

    skore logo

  

  
the scikit-learn sidekick



Elevate ML Development with Tracking and Built-in Recommended Practices \

[Documentation](https://skore.probabl.ai) — [Community](https://discord.probabl.ai)










## Why skore?



ML development is an art — blending business sense, stats knowledge, and coding skills. Brought to you by [Probabl](https://probabl.ai), a company co-founded by scikit-learn core developers, skore helps data scientists focus on what matters: building impactful models with hindsight and clarity.



Skore is just at the beginning of its journey, but we’re shipping fast! Frequent updates and new features are on the way as we work toward our vision of becoming a comprehensive library for data scientists, supporting every phase of the machine learning lifecycle.



⭐ Support us with a star and spread the word - it means a lot! ⭐



## Key features



- **Track and Visualize Results**: Capture your intermediate ML/DS results without the overhead, while gaining deeper insights through intuitive visualizations of your experiments.

- **Elevate Model Development**: Avoid common pitfalls and follow recommended practices with automatic guidance and insights.

    - Enhancing key scikit-learn features with `skore.CrossValidationReporter` and `skore.train_test_split()`.



![GIF: short demo of skore](https://media.githubusercontent.com/media/probabl-ai/skore/main/sphinx/_static/images/2024_12_12_skore_demo_comp.gif)



## 🚀 Quick start



### Installation



#### With pip



We recommend using a [virtual environment (venv)](https://docs.python.org/3/tutorial/venv.html). You need `python>=3.9`.



Then, you can install skore by using `pip`:

```bash

pip install -U skore

```



#### With conda



skore is available in `conda-forge`:



```bash

conda install conda-forge::skore

```



You can find information on the latest version [here](https://anaconda.org/conda-forge/skore).



### Get assistance when developing your ML/DS projects



1. From your Python code, create and load a skore project:

    ```python

    import skore

    my_project = skore.create("my_project", overwrite=True)

    ```

    This will create a skore project directory named `my_project.skore` in your current working directory.



2. Evaluate your model using `skore.CrossValidationReporter`:

    ```python

    from sklearn.datasets import load_iris

    from sklearn.svm import SVC



    X, y = load_iris(return_X_y=True)

    clf = SVC(kernel="linear", C=1, random_state=0)



    reporter = skore.CrossValidationReporter(clf, X, y, cv=5)



    # Store the results in the project

    my_project.put("cv_reporter", reporter)



    # Display a plot result in your notebook

    reporter.plots.scores

    ```



3. Finally, from your shell (in the same directory), start the UI:

    ```bash

    skore launch "my_project"

    ```

    This will open skore-ui in a browser window.



You will automatically be able to visualize some key metrics (although you might have forgotten to specify all of them):

![Cross-validation screenshot](https://media.githubusercontent.com/media/probabl-ai/skore/main/sphinx/_static/images/2024_12_12_skore_cross_val_clf.png)



Also check out `skore.train_test_split()` that enhances scikit-learn. Learn more in our [documentation](https://skore.probabl.ai).



## Contributing



Thank you for considering contributing to skore! Join our mission to promote open-source and make machine learning development more robust and effective. Please check the contributing guidelines [here](https://github.com/probabl-ai/skore/blob/main/CONTRIBUTING.rst).



## Feedback & Community



-   Join our [Discord](https://discord.probabl.ai/) to share ideas or get support.

-   Request a feature or report a bug via [GitHub Issues](https://github.com/probabl-ai/skore/issues).







  ![license](https://img.shields.io/pypi/l/skore)

  ![python](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue?style=flat&logo=python)

  [![downloads](https://static.pepy.tech/badge/skore/month)](https://pepy.tech/projects/skore)

  [![pypi](https://img.shields.io/pypi/v/skore)](https://pypi.org/project/skore/)

  ![ci](https://github.com/probabl-ai/skore/actions/workflows/ci.yml/badge.svg?event=push)

  [![Discord](https://img.shields.io/badge/Discord-%235865F2.svg?logo=discord&logoColor=white)](https://discord.probabl.ai/)



---



Brought to you by





    

        

        Probabl logo