Use it when
- You want to track ML experiment metrics like loss and accuracy.
- You want to visualize the tracked metrics and model architecture.
- You want to view model histograms.
- You want to log diagnostic data as images.
- You want an integrated What-if Tool to analyze black-box classification and regression ML models.
- You want an integrated debugger tool.
- What-if Tool requires TensorFlow Serving tool, and the dataset must be in a TFRecord file accessible by TensorBoard.
Airflow + MLflow stack