AWS Certified Machine Learning Engineer – Associate (MLA-C01) Free Practice Exam Questions

198 real AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam questions with answers and AI explanations. Amazon Web Services certification prep — page 18 of 20.

Question 180: An ML engineer is using Amazon SageMaker Canvas to build a custom ML model from an imported dataset. The ML engineer wants the model to make continuous numeric…
Question 181: A bank needs to use Amazon SageMaker AI to create an ML model to determine which customers qualify for a new product. The bank must use algorithms that SageMak…
Question 182: An ML engineer is building a model to predict house and apartment prices. The model uses three features: Square Meters, Price, and Age of Building. The dataset…
Question 184: An ML engineer is training a text generation model on Amazon SageMaker AI. After several epochs, the loss function does not converge, and the model’s accuracy…
Question 185: A company wants to migrate ML models from an on-premises environment to Amazon SageMaker AI. The models are based on the PyTorch algorithm. The company needs t…
Question 186: A company runs its ML workflows on an on-premises Kubernetes cluster. The ML workflows include ML services that perform training and inferences for ML models.…
Question 190: A company has trained an ML model that is packaged in a container. The company will integrate the model with an existing Python web application. The company ne…
Question 191: A company stores user clickstream data in an Amazon S3 bucket in AWS Account A. The company needs to use the data to train an ML model in Amazon SageMaker AI i…
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 credent…
Question 193: A company is using an Amazon SageMaker AI ML model to predict traffic accidents that potholes cause. An ML engineer has configured SageMaker Model Monitor to r…