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Exercise

MLFlow for logging and retrieving data

MLflow is an open-source platform for managing the ML lifecycle. It can be used to keep track of experiments, packaging code into reproducible runs, and sharing and deploying models. In the following exercise, you will log some of the parameters of a training experiment for your heart disease model. mlflow is imported, and the trained heart disease model has been loaded for you.

Instructions

100 XP
  • Initialize an MLflow experiment named "Logistic Regression Heart Disease Prediction".
  • Start a run, and log the trained models coefficient and intercept.