Databricks Certified Machine Learning Professional Practice Mode

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A0

  - Correct answer : A — Each stage runs in order: `Transformer` stages transform immediately, `Estimator` stages fit and are replaced by fitted transformers, giving a `PipelineModel`. A . `Pipeline.fit()` runs each stage in sequence: transformer stages like `OneHotEncoder` and `VectorAssembler` apply their transform immediately, while estimator stages like `StringIndexer` and `LogisticRegression` are fit on the data produced by prior stages and become fitted transformers inside the returned `PipelineModel`. B . Every stage in the list actually executes; the earlier stages are not skipped or treated as inert configuration, since each one produces the transformed columns the next stage depends on. C . Pipeline stages run sequentially because each stage typically consumes the output column of the previous one, so they cannot be executed in parallel as independent, unrelated steps. D . Mixing indexing, encoding, assembling, and a classifier in one `Pipeline` is the standard pattern the API is designed for, so no exception is raised for combining these stage types.