Machine Learning Engineer
easymachine-learning-engineer-experiment-tracking
Why is experiment tracking important and what should you log?
Answer
Experiment tracking makes results reproducible and comparable.
Log:
- Dataset version/hash
- Code + config
- Metrics and plots
- Model artifacts
- Runtime environment
Without tracking, teams can’t reliably reproduce “best” results or debug production regressions.
Related Topics
MLOpsReproducibilityExperiments