TimberTrek

TimberTrek, an open-source tool gaining stars on GitHub, combines interpretable machine learning with interactive visualization. It lets users explore Rashomon sets — collections of equally accurate decision trees — and choose the model that best matches their domain knowledge. The tool runs as a web app and in Jupyter notebooks, drawing attention from data scientists interested in making model choices more transparent.