← MLOps basics
Lesson 3 of 3
Experiment tracking
Watch, read the card, then practise. Experiment tracking · Model versioning
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Practise this topicExperiment tracking
Experiment tracking records every training run: settings, data version, metrics and outputs.
Remember: If it isn't logged, you can't reproduce it.
Model versioning
Versioning models (and their data and settings) tells you which model made each prediction and lets you roll back.
Remember: Rolling back should take minutes.
Try the example in Code Lab
runs = [{"id": 1, "lr": 0.1, "val": 0.84}, {"id": 2, "lr": 0.01, "val": 0.89}, {"id": 3, "lr": 0.001, "val": 0.86}]
best = max(runs, key=lambda r: r["val"])
print(best["id"], best["lr"])