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.