As part of the Explainable AI bootcamp organized by AI planet formerly DPhi around May, I had to work on a project that used Random Forest and SHAP that helped in identifying the factors that classified breast cancer as benign or malignant.
I had never heard of SHAP before this bootcamp but I am glad I got to know about it through this. I was always curious to know how we could infer which variables affected the dependent variable and to what extent. SHAP is a great tool in understanding the impact of every variable in deciding the class to put the data point in.
Take your time to explore the notebook and enjoy learning :)