Galen Seilis08/26/2023, 5:51 AM
on some of the separate data sources in the catalog) and an EDA pipeline that makes a datapane report (https://datapane.com/). When it comes to training multiple models iteratively, does it sound reasonable to have a pipeline per model? This isn't like a grid search or other hyperparameter tuning exercise (e.g. via https://optuna.org/) but rather each model is a thoughtful exercise based on the previously-trained models. Given that this is a manual, by design, approach for this particular collection of models, would you have separate pipelines or just separate with tags or have distinct models on different git branches or have separate kedro projects? Or something else? I'm sure there are many good and bad ideas. What would you do (and why, if you feel you can explain why)?
Juan Luis08/26/2023, 9:12 AM
Galen Seilis08/26/2023, 7:48 PM