Machine learning operations, or MLOps, is a set of practices to deploy and maintain machine learning models in production reliably and efficiently. The vetiver framework is for MLOps tasks in Python and R.
Vetiver, the oil of tranquility, is used as a stabilizing ingredient in perfumery to preserve more volatile fragrances.
The goal of vetiver is to provide fluent tooling to version, deploy, and monitor a trained model. Functions handle both recording and checking the model’s input data prototype, and predicting from a remote API endpoint.
Data scientists have effective tools that they ❤️ to:
collect data
prepare, manipulate, refine data
train models
There is a lack 😩 of effective tools to:
version and publish models
put models into production
monitor model performance
Use vetiver to version and deploy your trained models.