Comparing interpretable machine learning and regression models / GAMs
for the dataset in
https://www.kaggle.com/dgomonov/data-exploration-on-nyc-airbnb 

Interpretable machine learning: Usually fit black boxes and then use e.g. Shapley values to interpret the model result

GAM regression: Generalised additive models allow us to interpret parameters in a similar way to how we interpret parameters in linear regression.

Additional inspiration: https://christophm.github.io/interpretable-ml-book/index.html