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  3. Introduction to MLflow

Exercise

Creating an MLproject for the ML Lifecycle: Model Evaluation

In this exercise, you will continue creating your MLproject file to manage steps of the ML lifecycle. You will create another entry point called model_evaluation. This step in the workflow accepts the run_id output from the model_engineering step and runs model evaluation using training data from our Insurance dataset.

You can print the current MLproject file using the IPython Shell and executing print(MLproject).

Instructions

100 XP
  • Create an entry point called model_evaluation.
  • Set parameters for run_id.
  • Place the parameter within the command.