Google Cloud Professional Machine Learning Engineer — Question 34

You are developing ML models with AI Platform for image segmentation on CT scans. You frequently update your model architectures based on the newest available research papers, and have to rerun training on the same dataset to benchmark their performance. You want to minimize computation costs and manual intervention while having version control for your code. What should you do?

Answer options

• A. Use Cloud Functions to identify changes to your code in Cloud Storage and trigger a retraining job.
• B. Use the gcloud command-line tool to submit training jobs on AI Platform when you update your code.
• C. Use Cloud Build linked with Cloud Source Repositories to trigger retraining when new code is pushed to the repository.
• D. Create an automated workflow in Cloud Composer that runs daily and looks for changes in code in Cloud Storage using a sensor.

Correct answer: C

Explanation

The correct answer is C because using Cloud Build with Cloud Source Repositories allows for automated retraining whenever new code is pushed, minimizing manual intervention. Option A is inefficient as it relies on Cloud Functions, which may not be as straightforward for tracking code changes. Option B requires manual submission of jobs, which does not minimize manual effort. Option D, while automated, runs daily and may not respond promptly to code changes compared to the triggering mechanism in Cloud Build.