Google Professional Machine Learning Engineer exam dumps

Google Professional Machine Learning Engineer practice question 37 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 37

Select 3Google Cloud Platform

You are tasked with building a content moderation application for a social media platform. The application should automatically detect and flag inappropriate images and text in real-time. Your team decides to leverage Google Cloud’s Model Garden to accelerate development. What steps should you take to implement this solution using pre-trained ML APIs available in Model Garden?

  1. A

    Use the Vision API from Model Garden to detect inappropriate content in images and integrate it into your application.

  2. B

    Train a custom model on TensorFlow for text moderation and deploy it on Vertex AI.

  3. C

    Use the Natural Language API from Model Garden to analyze text for inappropriate content and integrate it into your application.

  4. D

    Download a pre-trained model from Model Garden and fine-tune it for your specific content moderation use case.

  5. E

    Leverage the Model Garden APIs directly by calling pre-trained models for both image and text content moderation without additional training.

Show answer and explanation

Correct answers: A, C, E

Explanation

Leveraging pre-trained ML APIs from Model Garden is a practical and efficient approach for building a content moderation application. The Vision API can handle image moderation tasks, while the Natural Language API is suited for text analysis. Additionally, Model Garden allows developers to directly call pre-trained models via APIs, eliminating the need for complex model training or fine-tuning in this scenario.

  • A. Correct.

    Correct: The Vision API available in Model Garden can be used to detect inappropriate content in images, making it an efficient choice for this use case.

  • B. Incorrect.

    Incorrect: While training a custom model is an option, leveraging pre-trained APIs from Model Garden is faster and more cost-effective for this scenario.

  • C. Correct.

    Correct: The Natural Language API from Model Garden can analyze text for inappropriate content, which aligns with the requirements of this application.

  • D. Incorrect.

    Incorrect: While fine-tuning may be necessary in some cases, the pre-trained ML APIs from Model Garden are designed to be used out-of-the-box for common use cases, avoiding the need for fine-tuning.

  • E. Correct.

    Correct: Model Garden provides pre-trained models that can be directly called through APIs for tasks like image and text moderation, simplifying the integration process.

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