Dissecting the internal logic of machine learning

Chapter 3 will give you the knowledge and tools to unpack the functioning and logic of machine learning, the key goal of explainable AI. We start by differentiating between glass box and black box AI algorithms so that you can better understand when and why XAI is needed. We’ll cover different XAI methods that can be used to extract information from AI models. We then explore how these methods work in practice, and give you some guidelines on how to interpret their outputs.