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1.

You plan to use hyperparameter tuning to find optimal discrete values for a set of hyperparameters. You want to try every possible combination of a set of specified discrete values. Which kind of sampling should you use?

Random sampling

Grid sampling

Bayesian sampling

2.

You're using hyperparameter tuning to train an optimal model based on a target metric named "AUC". What should you do in your training script?

Import the logging package and use a logging.info() statement to log the AUC.

Include a print() statement to write the AUC value to the standard output stream.

Use a mlflow.log_metric() statement to log the AUC value.

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