https://github.com/lewagon/data-templates
Curated templates for data analysis / science
https://github.com/lewagon/data-templates
Last synced: 9 months ago
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Curated templates for data analysis / science
- Host: GitHub
- URL: https://github.com/lewagon/data-templates
- Owner: lewagon
- License: mit
- Created: 2022-05-26T13:57:07.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-03-16T13:13:24.000Z (almost 3 years ago)
- Last Synced: 2025-04-06T11:24:16.939Z (9 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 565 KB
- Stars: 44
- Watchers: 10
- Forks: 33
- Open Issues: 1
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## What is this repo about ?
Le Wagon is hereby curating a selected list of useful **open-source templates** for data analysis / data science.
✅ These templates should be:
- self-explanatory
- replicable (provided Le Wagon [data-setup](https://github.com/lewagon/data-setup) has been done on the machine)
- focused on one specific theme
A theme could be:
- A **project boilerplate**: A typical 2 weeks-long / 4 students project in the spirit of what is done at [Le Wagon Data Science bootcamp](https://www.lewagon.com/data-science-course/full-time)
- e.g. "Time-Series cross-validation boilerplate"
- e.g. "Reinforcement Learning boilerplate"
- e.g. "Image classification trainer + streamlit API boilerplate"
- ...
- A **tutorials** guide focused on one specific topic worth sharing
- e.g. "Removing bottlenecks with Numba, Cython, and TensorFlow"
## How to contribute ?
Feel free to contribute by adding your suggestions
### Submit a pull request with new templates or improve existing ones
👉 Fork this repository to your account, and submit pull-requests following [the standard open-source contribution](https://jarv.is/notes/how-to-pull-request-fork-github/) methodology
👉 Le Wagon team will check your PR and integrate it to the list if it pass quality standards
### Discuss features/improvements/suggestions
👉 https://github.com/lewagon/data-templates/discussions