A Simple Explanation of Causal Inference in Python

There have been more deaths caused by the vaccine than the disease! So should the vaccine programme be cancelled to save lives? To solve that we need to ask the question "What would have happened if we had not run the vaccine programme?". That is a counter-factual question i.e. it is asking us to imagine a different world where we made a key choice differently and to find out what impact that would have had. I will tackle counter-factuals in detail in a future article but for now it is enough to say that the counter-factual makes this a causal inference model that is not well suited to machine learning techniques because it is ab out causation and not correlation.