Model Interpretability & Monitoring for AI & ML

Imagine training a computer to identify different types of flowers based on pictures. It works great, but how do you know exactly why the AI chooses a specific flower? This is where model interpretability comes in – it helps us peek inside the "black box" of AI models and understand their decision-making process. Another crucial aspect is model monitoring – just like monitoring a car's engine, we need to track the performance of AI models to ensure they continue to function reliably.

Opening the Black Box: Model Interpretability

Model interpretability refers to the ability to understand and explain the decisions made by AI models. This is important for several reasons: