Google Professional Machine Learning Engineer
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Ultimate access to all questions.
You are tasked with developing a machine learning model for image segmentation on CT scans using Google's AI Platform. Your objectives are to minimize operational costs, reduce manual intervention, and maintain strict version control for your code. Additionally, you plan to stay abreast of the latest research to refine your model architectures and retrain them on the same dataset for performance benchmarking. Considering these requirements, which strategy would best achieve your objectives? (Choose one correct option)
A
Implement Cloud Functions to automatically detect changes in your code stored in Cloud Storage and initiate a retraining job on AI Platform without manual oversight.
B
Configure a Cloud Composer workflow that uses a sensor to check for code changes in Cloud Storage daily and automatically starts a retraining job if changes are detected.
C
Manually use the gcloud command-line tool to submit training jobs to AI Platform each time you update your model code, ensuring direct control over the training process.
D
Leverage Cloud Build integrated with Cloud Source Repositories to automatically trigger model retraining on AI Platform upon each new commit to the repository, ensuring version control and minimal manual intervention.