Keeping track of what was tried.
WHAT TO RECORD FOR EVERY EXPERIMENT
The code version The data reference Parameters The environment Metrics Artefacts produced
WHY
Without it, results cannot be reproduced or compared.
WHAT TOOLS PROVIDE
That record automatically, with comparison and visualisation.
WHAT A MODEL REGISTRY ADDS
Versioned models with stage: development, staging, production, archived.
WHAT PROMOTION MEANS
Moving a version through those stages, with checks.
WHAT TO ATTACH TO EVERY VERSION
Its evaluation results Its training data reference Known limitations Who approved it
WHAT LINEAGE PROVIDES
Tracing a prediction back to a model, to code, to data.
WHY THAT MATTERS
It is what answers questions about a disputed decision.
WHAT TO VERSION ALONGSIDE MODELS
Feature definitions Preprocessing code Evaluation datasets
WHY EVALUATION DATASETS SPECIFICALLY
Comparing models requires the same test data.
WHAT TO NEVER ALLOW
Models trained on someone's machine and deployed without record.
WHAT TO ESTABLISH
That every production model can be reproduced from what is recorded.
