# 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