Correct Answer: D. HyperOpt
HyperOpt is a Python library optimized for efficiently tuning machine learning model hyperparameters. It excels in parallelizing this process across multiple computing resources, including Spark clusters, by supporting distributed hyperparameter searches. This makes HyperOpt the ideal choice for leveraging Spark clusters to tune single-node models.

Other Options:

• A (AutoScaling Clusters): While beneficial for resource management, auto-scaling clusters do not directly facilitate hyperparameter tuning.
• B (Delta Lake): Delta Lake enhances data reliability with ACID transactions in big data workloads but is unrelated to hyperparameter tuning.
• C (MLFlow Experiment Tracking): MLFlow is excellent for tracking experiments and managing the ML lifecycle but does not specialize in parallelizing hyperparameter tuning.