domino-experiment-tracking

Features and purpose

Track traditional ML experiments in Domino using the MLflow-based Experiment Manager. Covers experiment setup, auto-logging for sklearn/TensorFlow/PyTorch, manual logging, artifact storage, run comparison, and model registration. Use when training ML models, logging metrics and parameters, comparing model runs, or registering models.

Quick start

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.