Google Cloud Professional Machine Learning Engineer — Question 80
You are a lead ML engineer at a retail company. You want to track and manage ML metadata in a centralized way so that your team can have reproducible experiments by generating artifacts. Which management solution should you recommend to your team?
Answer options
- A. Store your tf.logging data in BigQuery.
- B. Manage all relational entities in the Hive Metastore.
- C. Store all ML metadata in Google Cloud’s operations suite.
- D. Manage your ML workflows with Vertex ML Metadata.
Correct answer: D
Explanation
The correct answer is D, as Vertex ML Metadata is specifically designed to manage ML workflows and metadata, ensuring reproducibility and artifact generation. Options A and C focus on logging and operations monitoring, which do not provide a centralized metadata management solution. Option B, while useful for managing relational data, does not cater specifically to the needs of ML workflows and metadata tracking.