Set up MLflow tracking and a model registry for the team
Technology
On MLflowMLflow Tracking · Model Registry
Define the path from experiment to production model
Train data scientists on logging runs and promoting models
Audit a solution
MLflow · MLOps
Audit the scope or technology with findings and recommendations.
DeliverableExecution
max 160 h
Support a solution
MLflow · MLOps
Focused support during design, build or run activities.
DeliverableExecution
max 160 h
Manage change
MLflow · MLOps
Perform a defined change with controlled execution.
DeliverableExecution
max 40 h
Manage releases
MLflow · MLOps
Release-management activities on the selected technology.
DeliverableExecution
max 80 h
Simulate failures
MLflow · MLOps
Simulate defined failures to assess resilience before production impact.
DeliverableExecution
max 40 h
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