In the third part of our blog series, we cover an essential topic that has gained significant traction in the ML-community in the past years: Explainability. Explainable AI is essential to establish trust in the models we develop. We discuss various approaches for CNN networks, with a particular focus on the Grad-CAM method.
A new field of Machine Learning is born: Causal Machine Learning. Learn here about the Causal Forest, one of the most famous Causal Machine Learning algorithms for estimating heterogeneous treatment effects.
A new field of Machine Learning is born: Causal Machine Learning. Learn here what it is and why it is crucial for the future of Data Science.