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| .github/workflows | ||
| modules | ||
| .pre-commit-config.yaml | ||
| MODEL_REGISTRY.md | ||
| README.md | ||
ML Toolkit
Creating a ML-toolkit that can be reused:
-
ML pipeline:
- A generic pipeline that has data version control, experiment tracking and a model registry
-
ML monitoring:
- A bolt-on service that can implement model monitoring
There are multiple protected branches which adapt the generic pipeline to produce different models:
- sap_change-**
- heat_change-**
- carbon_change-**
These branches will differ by the configuration files that define the data used and the outputs of the ML-pipeline
- There can be different additional logic for each branch but the pipeline will be the same.
Deployment
TBD