Behold, the NBDEV Linear Regression Tutorial for students of CSCI 435!
- Install JupyterLab
- conda install -c conda-forge -y jupyterlab OR pip install jupyterlab
- Install nbdev
- Mac and Linux:
- conda install -c fastai -y nbdev OR pip install nbdev
- Windows:
- pip install nbdev==2.3.7
- Mac and Linux:
- Install quarto
- nvdev_install_quarto
- Windows will redirect you to install it at the Quarto website
- Make sure to restart your terminal afterwards
- pip install jupyterlab-quarto
- nvdev_install_quarto
- Install the required modules if you don’t have them already
- Use either pip or conda
- matplotlib and numpy
- Python has csv and datetime already
- Create a new repository and clone it to your computer
- Go to the terminal and make sure you’re in your repo’s directory
- Run
nbdev_new
to generate necessary files - Replace
nbs/00_core.ipynb
andnbs/index.ipynb
with the ones in this repository, and addshampoo.csv
into thenbs
folder - Run
nbdev_readme
to generate a README.md that should look like this one - Run
jupyter lab
in the repository - Program
nbs/00_core.ipynb
such that everything works properly and save your PDF - Run
nbdev_install_hooks
- Push your changes to your Github
- Go to your Github Settings, click
Deploy from a branch
, and selectgh-pages
. - Return to Github Code, click the gear on About, and set the website to Github Pages
- Send the PDF and your Github Pages website to Alejandro and CC Prof. Poshyvanyk!
- https://nbdev.fast.ai/tutorials/tutorial.html
- https://jmp75.github.io/work-blog/posts/20221007-nbdev-windows/
- nbdev isn’t actually designed for Windows but this madlad somehow made it work anyways
P.S. I wrote this entire tutorial in one night.