Databricks Exam Databricks-Machine-Learning-Associate Topic 2 Question 19 Discussion

Actual exam question for Databricks's Databricks-Machine-Learning-Associate exam

Question #: 19
Topic #: 2

[All Databricks-Machine-Learning-Associate Questions]

A data scientist wants to tune a set of hyperparameters for a machine learning model. They have wrapped a Spark ML model in the objective function objective_function and they have defined the search space search_space.

As a result, they have the following code block:

Which of the following changes do they need to make to the above code block in order to accomplish the task?

AChange SparkTrials() to Trials()

BReduce num_evals to be less than 10

CChange fmin() to fmax()

DRemove the trials=trials argument

ERemove the algo=tpe.suggest argument

Show Suggested Answer

Suggested Answer: C

To find the run_id of the run with the best root-mean-square error (RMSE) in an MLflow experiment, the correct line of code to use is:

mlflow.search_runs( experiment_id, order_by=['metrics.rmse'] )['run_id'][0]

This line of code searches the runs in the specified experiment, orders them by the RMSE metric in ascending order (the lower the RMSE, the better), and retrieves the run_id of the best-performing run. Option C correctly represents this logic.

Reference

MLflow documentation on tracking experiments: https://www.mlflow.org/docs/latest/python_api/mlflow.html#mlflow.search_runs

by Rebbecca at Sep 15, 2024, 08:23 PM

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Lauran

10 days ago

The correct answer is A) Change SparkTrials() to Trials(). The question specifies that the data scientist is using a Spark ML model, so they need to use the SparkTrials() function instead of the regular Trials() function.

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