Guide to ML Explainability

How to Mitigate the “Black Box” Problem in Data Science

The model that predicts your target variable the best is not necessarily the model you should choose to deploy.

This is one of the most important (and surprising) things I’ve learned in my data science journey. Of course, you are building a machine learning model to make good predictions for the target variables you care about and if you can’t build a model that can satisfy that requirement…