Abstract
The widespread adoption of experiment tracking and MLOps platforms has streamlined the management of machine learning workflows. Yet, these platforms often fall short in supporting interactive visual analysis that combines experiment results, data exploration, and model explainability within a unified interface. To address this gap, we introduce ExperimentLens, an extensible experiment analytics tool that operates on top of existing tracking infrastructures and supports multiple platforms through a simple adapter interface.
ExperimentLens offers a rich, web-based environment for comparing runs, visualizing performance metrics, exploring datasets, and interpreting model outputs. Its modular architecture augments standard tracking systems with flexible, interactive capabilities that support both routine monitoring and in-depth analysis. We illustrate ExperimentLens’ functionality through a walkthrough of its architecture and user interface.