This package collects data sets and various helper functions for ISLP.
We generally recommend creating a Python environment to isolate any code │
from other dependencies. This is good practice. You can choose between uv (recommended) or conda. │
To create a uv environment in a Mac OS X or Linux environment run:
uv venv
To run python code in this environment, you must activate it:
source .venv/bin/activate
Having completed the steps above, we use pip to install the ISLP package:
uv pip install ISLP
If JupyterLab is not already installed, run the following after having activated your uv environment:
uv pip install jupyterlab
If not using uv but conda instead, create a Python environment called islp in the
Anaconda app. This can be done by selecting Environments on the left
hand side of the app's screen. After creating the environment, open a
terminal within that environment by clicking on the "Play" button.
The correspnding installation commands for ISLP and Jupyter are:
pip install ISLP jupyterlab
The ISLP labs use torch and various related packages for the lab on deep learning. The requirements
are included in the requirements for ISLP with the exception of those needed
for the labs which are included in the requirements for the labs which
will be set to the correct versions when a specific git tag is checked out.
See the docs for the latest documentation.
- Jonathan Taylor
- Trevor Hastie
- Gareth James
- Robert Tibshirani
- Daniela Witten
Thanks goes to these wonderful people (emoji key):
 danielawitten 💻 🖋 |
 trevorhastie 💻 🖋 |
 tibshirani 💻 🖋 |
This project follows the all-contributors specification. Contributions of any kind welcome!
