AI engineering glossary · MLOps, LLMOps cloud
What is experiment tracking?
Experiment tracking: Recording, for every training run, its code version, data version, settings, metrics and outputs so that results can be compared and reproduced later. Without it, teams cannot explain why one model beat another.
Experiment tracking: an example
A run log shows that learning rate 3e-4 gave 0.87 F1 on commit a1b2c3, while 1e-3 gave 0.84.
Related terms
- MLflow
- Weights & Biases
- Reproducibility
- Hyperparameter sweep
More MLOps, LLMOps cloud terms
Where you learn it
Experiment tracking is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.