Google Professional Machine Learning Engineer exam dumps

Google Professional Machine Learning Engineer practice question 310 of 522

Professional Machine Learning Engineer. Professional level, Google Cloud. Free question with the correct answer and a full explanation.

Google Professional Machine Learning Engineer Question 310

Select 4Google Cloud Platform

You are a machine learning engineer managing a model registry for your organization using Vertex AI. Your team needs to track and manage multiple versions of models effectively, ensure that the best-performing models are deployed to production, and maintain auditability of historical versions. Which practices should you implement to organize the model registry in Vertex AI?

  1. A

    Use model metadata to track performance metrics, such as accuracy, precision, and recall, for each model version.

  2. B

    Manually delete older model versions to keep the registry clean and prevent clutter.

  3. C

    Implement versioning for models by assigning unique version identifiers to each new iteration.

  4. D

    Tag models with labels to indicate their stage in the lifecycle (e.g., 'staging', 'production', 'archived').

  5. E

    Configure automated triggers to promote models based on performance thresholds.

Show answer and explanation

Correct answers: A, C, D, E

Explanation

To effectively organize a model registry in Vertex AI, it is essential to track performance metrics, implement versioning, and use lifecycle labels to maintain organization and clarity. Additionally, automating model promotion based on performance thresholds ensures that the best models are deployed to production while retaining auditability. Avoid manual interventions, such as deleting older versions, as this can compromise traceability and historical insights.

  • A. Correct.

    Tracking performance metrics using model metadata ensures that your team can compare and evaluate models effectively, which is critical for selecting the best-performing ones.

  • B. Incorrect.

    Manually deleting older model versions is not recommended, as this can lead to loss of historical data and reduce traceability. Instead, use automated versioning and archival strategies.

  • C. Correct.

    Assigning version identifiers to models ensures auditability and makes it easier to manage multiple iterations of a model over time.

  • D. Correct.

    Tagging models with lifecycle labels helps organize the registry and provides clarity on the current status of each model.

  • E. Correct.

    Automated triggers allow for efficient promotion of models based on predefined performance thresholds, reducing manual effort and ensuring consistency.

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