XAI is the study of how to make machine learning models explainable to humans. It is a subfield of AI that is concerned with the interpretability of machine learning models. It helps in interpretability, explainability, and transparency of a given model. In general, ML models are considered as black boxes. Its like you feed in training data and get outputs on unseen data. Unlike explicit programming, where you define the rules on how something works, ML models are trained and the ‘stuff’ in it d...