Embedded Files
Whilst the AMRC projects are largely involved in proving a concept, as the organisation and its partners move to a more DCM-based approach there will be a need to deploy some of the algorithms and models that are built. This will require extra consideration and expertise.
Some Things to Consider:
Some Things to Consider:
ML Ops
Concept Drift
Model Drift
Using the workflow - deploying the models
Using the workflow - deploying the models
Deployment & Maintenance Strategy
Deployment & Maintenance Strategy
Outputs from successful data-centric projects have the potential to generate value for the organisation through deployment, which brings a host of new challenges to address. This template provides a foundation for strategising on deploying and maintaining DCM applications in production, to help maximise the impact of your research.
Guidance and learning resources
Guidance and learning resources
Deployment with Docker
Deployment with Docker
The DCM workflow contains a number of built-in coding tools to streamline your analytics process. Check out the guidance for deploying a containerised application with Docker.
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