David Neuzerling

David Neuzerling

Data, Maths, R

MLflow is a platform for the “machine learning cycle”. It’s a suite of tools for managing models, with tracking of hyperparameters and metrics, a registry of models, and options for serving. It’s this last bit that I’m going to focus on today.

I’m creating an R API wrapper around my state’s public transport service. To make life easier for the users, the responses from the API calls are parsed and returned as tibbles/data frames. To make life easier for me, I need to keep track of the API call behind each tibble. I do this by using the tibble::new_tibble() function to attach metadata to the tibble as attributes, and creating a custom print method to make the metadata visible.

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