Google Cloud Professional Machine Learning Engineer — Question 229

You are building a custom image classification model and plan to use Vertex AI Pipelines to implement the end-to-end training. Your dataset consists of images that need to be preprocessed before they can be used to train the model. The preprocessing steps include resizing the images, converting them to grayscale, and extracting features. You have already implemented some Python functions for the preprocessing tasks. Which components should you use in your pipeline?

Answer options

• A. DataprocSparkBatchOp and CustomTrainingJobOp
• B. DataflowPythonJobOp, WaitGcpResourcesOp, and CustomTrainingJobOp
• C. dsl.ParallelFor, dsl.component, and CustomTrainingJobOp
• D. ImageDatasetImportDataOp, dsl.component, and AutoMLImageTrainingJobRunOp

Correct answer: B

Explanation

The correct option is B because DataflowPythonJobOp can handle the preprocessing of images in a scalable way, while WaitGcpResourcesOp ensures that the necessary resources are available, and CustomTrainingJobOp is used for training the model. The other options either do not provide the appropriate tools for preprocessing or do not include the necessary orchestration for training.