Hi,
I have built a model in my work using tidymodels to identify fraud within our data.
It works so well I have been asked me to create it for another nine departments 
I only have my PC to build and train these models but recognize that maintaining 11 models on a weekly basis on top of my normal work might prove haphazard and time consuming. I am not an ML Ops expert by any stretch of the imagination but my setup is on windows. Modelling in general for me involves using the windows scheduler and comprises roughly of the following steps
Training every month
- Pull the data from the data-warehouse/scrape from websites
- Build the features - (
tidyverse) - Train the model - (
tidymodels) - Apply Sensitivity Analysis - (
probably) - Save the model
Daily Run
- Pull daily data, execute the model
- Email results to the business (
blastula+ggplot)
I have seen a recent post on vetiver which is MLOps in both R and Python
Is the expansion of my modelling task a good use case for
vetiver?
I guess my requirements around this are basically to
- Catch data drift
- Catch a model failure
- Make my life a bit easier for maintaining the modelling
I have no budget
Thank you for your time