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ISLP_labs/README.md
Jonathan Taylor 93fcff9b8e use uv run jupyter
2026-02-02 17:33:41 -08:00

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# ISLP_labs
[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/intro-stat-learning/ISLP_Labs)
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[![All Contributors](https://img.shields.io/badge/all_contributors-4-orange.svg?style=flat-square)](#contributors-)
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## Authors
- Trevor Hastie
- Gareth James
- Jonathan Taylor
- Robert Tibshirani
- Daniela Witten
### ISLP
Please ensure you have followed the installation instructions for
[ISLP](https://github.com/intro-stat-learning/ISLP). This will address
installation of [jupyterlab](https://github.com/jupyterlab/jupyterlab)
if necessary, which is not included as a requirement of the labs.
### Up-to-date version of labs for ISLP.
This repo will track labs for ISLP as their source code changes. The
intent is that building a virtual environment with
`requirements.txt` will reproduce the results in this repo.
To install the current version of the requirements run
```
uv pip install -r https://raw.githubusercontent.com/intro-stat-learning/ISLP_labs/v2.2.1/requirements.txt;
```
The labs can now be run via:
```
uv run jupyter lab Ch02-statlearn-lab.ipynb
```
# Zip / tarball
You can download all the labs as a `.zip` or `.tar.gz` [here](https://github.com/intro-stat-learning/ISLP_labs/releases/tag/v2.2.1)
## Contributors ✨
Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):
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<td align="center" valign="top" width="14.28%"><a href="https://github.com/tibshirani"><img src="https://avatars.githubusercontent.com/u/2848609?v=4?s=100" width="100px;" alt="tibshirani"/><br /><sub><b>tibshirani</b></sub></a><br /><a href="https://github.com/intro-stat-learning/ISLP_labs/commits?author=tibshirani" title="Code">💻</a> <a href="#content-tibshirani" title="Content">🖋</a></td>
<td align="center" valign="top" width="14.28%"><a href="https://web.stanford.edu/~hastie/"><img src="https://avatars.githubusercontent.com/u/13293253?v=4?s=100" width="100px;" alt="trevorhastie"/><br /><sub><b>trevorhastie</b></sub></a><br /><a href="https://github.com/intro-stat-learning/ISLP_labs/commits?author=trevorhastie" title="Code">💻</a> <a href="#content-trevorhastie" title="Content">🖋</a></td>
<td align="center" valign="top" width="14.28%"><a href="https://github.com/danielawitten"><img src="https://avatars.githubusercontent.com/u/12654191?v=4?s=100" width="100px;" alt="danielawitten"/><br /><sub><b>danielawitten</b></sub></a><br /><a href="https://github.com/intro-stat-learning/ISLP_labs/commits?author=danielawitten" title="Code">💻</a> <a href="#content-danielawitten" title="Content">🖋</a></td>
<td align="center" valign="top" width="14.28%"><a href="http://statweb.stanford.edu/~jtaylo"><img src="https://avatars.githubusercontent.com/u/341611?v=4?s=100" width="100px;" alt="Jonathan Taylor"/><br /><sub><b>Jonathan Taylor</b></sub></a><br /><a href="https://github.com/intro-stat-learning/ISLP_labs/commits?author=jonathan-taylor" title="Code">💻</a> <a href="#content-jonathan-taylor" title="Content">🖋</a></td>
</tr>
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</table>
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This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!