TL;DR — Experiment Tracking

Design an experiment tracking system that records and organizes ML experiment metadata — hyperparameters, metrics, code versions, artifacts, and environment configurations. Data scientists use it to compare experiments, reproduce results, and collaborate on model development. Key features: Log hyperparameters, metrics, and artifacts from training code. Real-time metric streaming with live dashboard updates.