ml-pipeline

This is a short tutorial on the wonders of sklearn.compose and configuration-based preprocessing in machine learning.

Getting started

There are two main notebooks, ml-pipeline.ipynb and ml-pipeline-slides.ipynb. The former is a much verbose dive into the content, whereas the latter is intended to be viewed as Jupyter Notebook slides.

To view/run both notebooks from within the Jupyter Notebook server, simply type:

$ sh setup.sh && sh start-server.sh

From there, you'll be able to open whichever notebook you like and view the content.

If you'd prefer to view the slides, simply type:

$ sh setup.sh && sh to-slides.sh

Questions/suggestions

Please open an issue if you have any suggestions or questions.