Databricks Certified Machine Learning Associate Exam Databricks-Machine-Learning-Associate Exam Questions with Experts Answers Updated Recently

A data scientist is utilizing MLflow Autologging to automatically track their machine learning experiments. After completing a series of runs for the experiment experiment_id, the data scientist wants to identify the run_id of the run with the best root-mean-square error (RMSE).

Which of the following lines of code can be used to identify the run_id of the run with the best RMSE in experiment_id?

A)

B)

C)

D)

A data scientist is using the following code block to tune hyperparameters for a machine learning model:

Which change can they make the above code block to improve the likelihood of a more accurate model?

A data scientist learned during their training to always use 5-fold cross-validation in their model development workflow. A colleague suggests that there are cases where a train-validation split could be preferred over k-fold cross-validation when k > 2.

Which of the following describes a potential benefit of using a train-validation split over k-fold cross-validation in this scenario?

A data scientist has created a linear regression model that useslog(price)as a label variable. Using this model, they have performed inference and the predictions and actual label values are in Spark DataFramepreds_df.

They are using the following code block to evaluate the model:

regression_evaluator.setMetricName("rmse").evaluate(preds_df)

Which of the following changes should the data scientist make to evaluate the RMSE in a way that is comparable withprice?