The presentation slides are available here: https://bujniewicz.github.io/mdm-ml-for-developers/
The repository consists of:
- github pages files: index.html which is the jupyter notebook converted to slides and mdm-ml-url.svg which is a QR code containing a link to this very repository.
- requirements.txt for dependency tracking.
- ML in Python for developers.ipynb - jupyter notebook containing the editable presentation.
- Two machine learning models and validators:
- bayes - this is a naive bayes model of salary classification, using https://archive.ics.uci.edu/ml/datasets/adult. There are actually two models here, naive and regular version. They use different initial data processing.
- knn - this is a knn model of altitude regression, using https://archive.ics.uci.edu/ml/datasets/3D+Road+Network+%28North+Jutland%2C+Denmark%29
I was using Python 3.7.1 for running the code contained in this repository. However, I've verified it works in 3.6.7 as well. It will not work before CPython 3.6 due to reliance on class parameter declaration order.
To work on the repo, create an environment of your preference (docker, virtualenv, venv module, etc.) and
pip install -r requirements.txt.
To start the jupyter notebook, run jupyter notebook.
To build the presentation, run make slides.
Feel free to contact me on https://twitter.com/bujniewicz.