/experimenting-with-rubicon

using the Rubicon logging library on some simple classification models

Primary LanguagePython

experimenting-with-rubicon

This repo illustrates how rubicon_ml's dashboard can make tracking your model code easy!

my_model.py contains a simple Scikit-learn classification model and trains it across a few parameter sets with a grid search. These results are then logged with rubicon_ml's git integration enabled. As more commits are made to this repo that change the classifier and the parameter sets, each group of experiments logged by my_model.py will contain a direct reference to the code on GitHub that produced them. These references are used by the rubicon_ml dashboard to generate links to the code on GitHub.

More info on the Palmer penguins dataset used in this example can be found here.

setup

conda env create -f environment.yml
conda activate experimenting-with-rubicon

run

python my_model/my_model.py