Databricks Certified Machine Learning Associate — Question 24

Which of the following tools can be used to parallelize the hyperparameter tuning process for single-node machine learning models using a Spark cluster?

Answer options

• A. MLflow Experiment Tracking
• B. Spark ML
• C. Autoscaling clusters
• D. Hyperopt
• E. Delta Lake

Correct answer: D

Explanation

Hyperopt is designed specifically for optimizing hyperparameters and can run its tuning processes in parallel across a Spark cluster. The other options, while useful in various contexts, do not focus on the parallelization of hyperparameter tuning; MLflow is for tracking experiments, Spark ML is for machine learning tasks, autoscaling relates to resource management, and Delta Lake is for data storage and management.