Original tutorial material from Jake VanderPlas
- email: jakevdp@uw.edu
- twitter: @jakevdp
- github: jakevdp
This repository contains notebooks and other files associated with the Scikit-learn tutorial. The notebooks have been updated by NeSI (http://github.com/nesi/sklearn_tutorial.git) to run with recent versions of Python and dependencies.
Read NESI.md to find out how to run the notebooks on NeSI. All the packages required by the tutorial are already installed on NeSI JupyterHub.
If you prefer to run on your own computer then we recommend that you download and install Miniconda. Once Miniconda is installed, navigate to your local copy of the repository and use the following command to create a Conda environment with all required packages:
conda env create -f environment.yml
Then activate your environment:
conda activate skl_tut
The tutorial material has been tested on NeSI with the following package versions:
- Python version 3.10.5
numpyversion 1.22.4: https://www.numpy.orgscipyversion 1.8.1: https://www.scipy.orgmatplotlibversion 3.5.2: https://matplotlib.orgscikit-learnversion 1.1.1: https://scikit-learn.orgjupyterlabversion 3.4.3: https://jupyterlab.readthedocs.ioipywidgetsversion 7.7.0: https://ipywidgets.readthedocs.iopandasversion 1.4.2: https://pandas.pydata.org/
We have already installed all the notebooks on NeSI JupyterHub. However, if you prefer to run on your laptop, you will need to clone the repository:
git clone https://github.com/nesi/sklearn_tutorial.git
Note also that some of the code in these notebooks will not work outside the directory structure of this tutorial, so it is important to clone the full repository if possible.
If you have followed the installation instructions to run on your laptop, start JupyterLab:
jupyter lab
Then navigate the directory structure.
The notebooks are under the directory notebooks.
Click on Index.ipynb to get started.