Google Cloud Professional Machine Learning Engineer — Question 179

You work at a bank. You need to develop a credit risk model to support loan application decisions. You decide to implement the model by using a neural network in TensorFlow. Due to regulatory requirements, you need to be able to explain the model’s predictions based on its features. When the model is deployed, you also want to monitor the model’s performance over time. You decided to use Vertex AI for both model development and deployment. What should you do?

Answer options

• A. Use Vertex Explainable AI with the sampled Shapley method, and enable Vertex AI Model Monitoring to check for feature distribution drift.
• B. Use Vertex Explainable AI with the sampled Shapley method, and enable Vertex AI Model Monitoring to check for feature distribution skew.
• C. Use Vertex Explainable AI with the XRAI method, and enable Vertex AI Model Monitoring to check for feature distribution drift.
• D. Use Vertex Explainable AI with the XRAI method, and enable Vertex AI Model Monitoring to check for feature distribution skew.

Correct answer: A

Explanation

The correct answer is A because using Vertex Explainable AI with the sampled Shapley method allows for effective explanation of the model’s predictions, while enabling Vertex AI Model Monitoring to check for feature distribution drift helps ensure the model remains reliable over time. Options B, C, and D do not correctly combine the necessary explanation method and monitoring for drift, which is critical for regulatory compliance.