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GUIDE bu am solo
Cycle de vie ci modèle dafay jël: faramfale laaj bi, prepare data, entraîner walla tann, évaluer, déployer, surveiller, ak retire.
Déglul tegtal biiIA-nettali · ~2 min
It describes ongoing responsibility for a system, not merely the completion of a training run. Each stage needs evidence that can be traced to a particular version.
Start with a purpose, responsible owner, and decision about whether a model is needed at all. Define the operating conditions and what would make the project unsuitable. This prevents a technically interesting experiment from becoming a service without a clear use case. Version the data, preprocessing, model, prompts, and evaluation materials. These components interact: changing a feature calculation or retrieval index can alter behavior without changing the model weights. A release record should identify the complete configuration. Deploy gradually where practical, compare with the previous version, and retain a rollback route. Test startup, cancellation, timeouts, dependency failure, and compatibility with existing clients. Operational readiness includes the surrounding service and the people responding to incidents. After deployment, monitor both system health and task outcomes. Define who reviews alerts, when retraining or replacement is justified, and how old versions are retired. Deleting a model file does not automatically remove retained input data, cached outputs, or a dependent service. Track those assets explicitly.
04misaal biñ liggéey
Imagine a demand model trained on prices in dollars while a new service sends prices in cents.
The model file is unchanged, yet inputs are multiplied by 100. An input-range check can detect the mismatch before relying on forecasts.
Restore the compatible preprocessing version and add the incident as a regression test.
Li muy wane
This hypothetical failure shows why lifecycle management includes data contracts and dependencies.
Store a release manifest linking a model to its feature pipeline and evaluation set.
Use a staged rollout with an explicit rollback threshold.
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No. Monitoring, incident response, data changes, and retirement remain part of operating the system responsibly.
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Ci bi mu melGis bi ci topp
MLflow ak topp dundu model
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