A consistent, robust MLOps lifecycle for insights into travel behaviour
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GVB’s segmentation model uses travel behaviour to provide more insight into how passengers move around. This helps GVB offer suitable travel products, for example. The model needs to keep up with changes over the years. It also needs to be implemented robustly to meet GVB’s data architecture standards.
We set up a consistent, robust MLOps lifecycle so the segmentation model can be deployed to production and maintained effectively. We also created an MLOps workflow in Databricks with several reusable templates.
It was very interesting to improve the Databricks workflow for machine learning projects by putting a robust MLOps lifecycle in place. This has laid a solid foundation for setting up future projects in a similar way.
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