Visualizing Interpretability
Abstract This project aims to address gaps in machine learning (ML) interpretability with regard to visualization by investigating researchers workflows, tool usage, and challenges in understanding model behavior. Through a survey and interviews with practitioners, I identified limitations in existing visualization tools, such as fragmented workflows and insufficient support for...
Feb 3, 20253