https://github.com/pyladiesams/python-oss-sprints-mar2024

Sprints to contribute to the most popular data and AI Python OSS libraries
https://github.com/pyladiesams/python-oss-sprints-mar2024

conda dask geopandas jupyter matplotlib numpy pandas pymc sklearn

Last synced: 10 days ago
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Sprints to contribute to the most popular data and AI Python OSS libraries

• Host: GitHub
• URL: https://github.com/pyladiesams/python-oss-sprints-mar2024
• Owner: pyladiesams
• License: mit
• Created: 2023-10-03T08:16:03.000Z (about 1 year ago)
• Default Branch: master
• Last Pushed: 2024-02-23T16:25:44.000Z (9 months ago)
• Last Synced: 2024-02-23T17:35:46.485Z (9 months ago)
• Topics: conda, dask, geopandas, jupyter, matplotlib, numpy, pandas, pymc, sklearn
• Homepage:
• Size: 726 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Python Open Source Sprints

## What are Python Open Source Sprints?

Open source software, including Python and most Python libraries, is developed as a joint effort of thousands of programmers. Programmers like you spend time contributing to documentation, tests, bug fixes, and new features. It's a wonderful opportunity for you to contribute in a guided way to the Python library you use.

## Can I participate if I have never contributed to open source?

Sure. Anyone with some Python knowledge is welcome to participate. PyLadies Amsterdam and Picnic mentors will guide you through.

## Python libraries to contribute to 

[scikit-learn](https://scikit-learn.org/stable/) - machine learning in Python

[transformers](https://huggingface.co/docs/transformers/en/index) - state-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX

[pandas](https://pandas.pydata.org/) - flexible and powerful data analysis/manipulation library for Python

[numpy](https://numpy.org/) - the fundamental package for scientific computing with Python

[dbt-core](https://www.getdbt.com/product/what-is-dbt) - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications

[FastAPI](https://fastapi.tiangolo.com/) - high performance, easy to learn, fast to code, ready for production

*Bonus Python library*

[diepvries](https://diepvries.picnic.tech/) - The Picnic Data Vault framework

## Credits

These open source sprints were set up by @pyladiesams