AWS Certified Machine Learning - Specialty MLS-C01 — Topic 1 Question 283

Question

A mining company wants to use machine learning (ML) models to identify mineral images in real time. A data science team built an image recognition model that is based on convolutional neural network (CNN). The team trained the model on Amazon SageMaker by using GPU instances. The team will deploy the model to a SageMaker endpoint. The data science team already knows the workload traffic patterns. The team must determine instance type and configuration for the workloads. Which solution will meet these requirements with the LEAST development effort?

Accepted Answer

Correct answer: B. The correct answer is B. Option B: Register the model artifact and container to the SageMaker Model Registry. Use the SageMaker Inference Recommender Advanced job type. Provide the known traffic pattern for load testing to select the best instance type... Amazon SageMaker builds, trains and deploys machine learning models in a fully managed service. AWS Config tracks resource configuration changes and evaluates compliance. This option meets the real-time / low-latency performance requirement.

AWS Certified Machine Learning - Specialty MLS-C01 — Question 283