Interpreting Machine Learning Models: A Hands-On Guide

Understanding Model Decisions for Trustworthy Machine Learning Solutions

Interpreting models is crucial because machine learning alone does not offer a complete solution. The complex issues addressed with these models can’t be solved with traditional software development due to unknowns within the problem space. By clarifying a model’s decisions, we can bridge gaps in our understanding and build trust in the AI systems we develop. In this session, we will explore the importance of model interpretation and cover methods such as feature importance, feature summary, and local explanations.