Creating a multi-step workflow: Model Evaluation

In this exercise, you will create the Model Evaluation step of our multi-step workflow used to manage part of the ML lifecycle. You will use the run() method from the MLflow Projects module and set the entry point to model_evaluation. You will then take the model_engineering_run_id as a parameter that was generated as an output in the previous exercise and pass it to the command.

The MLproject created in the previous step is available in the IPython Shell using print(MLproject).

The mlflow module is imported.

Assign the run() method from MLflow Projects module to model_evaluation.
Set the entry point argument to "model_evaluation".
Set a parameter called "run_id" with a value of model_engineering_run_id.

Exercise

Creating a multi-step workflow: Model Evaluation

Instructions