Explain the difference between using scikit-learn and Spark ML for a machine learning task involving a large dataset. What are the limitations of scikit-learn in this context and how does Spark ML overcome these limitations?

Simulated

Scikit-learn is more efficient for large datasets; Spark ML provides scalability through distributed processing.

7.1%

Scikit-learn is limited by single-node processing; Spark ML leverages cluster computing to handle large datasets.

82.1%

There is no significant difference; both can handle large datasets effectively.

3.6%

Spark ML is limited by its complexity; scikit-learn is simpler and more efficient.

7.1%

Databricks Certified Machine Learning - Associate