R Short Talk: Interpretable machine learning model, example of using gradient boosted GAM in R

Interpretability is an oft-overlooked yet sometimes critical aspect in machine learning. It allows you to gain more insights about the underlying data generating process and more importantly increase the credibility of your model. A well-developed package in R allows you to build interpretable models with customized complexity in a few lines of code.