AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 192

A company has built, trained, and tuned two new ML models:

• Model A detects if a transaction is fraudulent based on the IP address, location, and user credentials. This model will be accessed every time a transaction occurs.
• Model B forecasts sales totals for the next month based on historical sales data. This model will be accessed one time each month.

The company must deploy both models to production by using Amazon SageMaker AI.

Which hosting solution for the models should the company use to meet these requirements?

Answer options

• A. Host both models in one container behind one real-time endpoint.
• B. Host Model A with an asynchronous endpoint. Host Model B with a real-time endpoint.
• C. Host Model A with a real-time endpoint. Use batch transform for Model B.
• D. Use batch transform for Model A. Host Model B with an asynchronous endpoint.

Correct answer: C

Explanation

The correct answer is C because Model A needs to be accessed frequently in real-time, making a real-time endpoint appropriate, while Model B, which is accessed only once a month, can efficiently use batch transform for processing. The other options do not align with the access frequency requirements of the models.