Amazon MLA-C01 Question Answers

Question # 71

A company has a binary classification model in production. An ML engineer needs to develop a new version of the model. The new model version must maximize correct predictions of positive labels and negative labels. The ML engineer must use a metric to recalibrate the model to meet these requirements. Which metric should the ML engineer use for the model recalibration?

A. Accuracy 
B. Precision 
C. Recall 
D. Specificity 

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Question # 72

An ML engineer uses an Amazon SageMaker AI notebook instance to run a training job that trains a neural network model with an estimator. The training job loads data iteratively from an Amazon S3 path that is configured as an environment variable. The ML engineer viewed a profiling report of the training job. The ML engineer discovered that a substantial amount of the training time is spent during data loading. How can the ML engineer improve the training speed?

A. Provision Amazon Elastic Block Store (Amazon EBS) Provisioned IOPS SSD io1 storage during the estimator initialization. Download the training data from the S3 path to Amazon EBS. Point the data loader to the EBS location. 
B. Provision Amazon Elastic File System (Amazon EFS) storage during the estimator initialization. Download the training data to Amazon EFS by using the S3 path. Point the data loader to the EFS location. 
C. Download the training data to the estimator by using fast file mode. Point the data loader to the location specified by the S3 path. 
D. Configure the path to the S3 bucket that contains the training data as a hyperparameter instead of an environment variable. 

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Question # 73

A company stores training data as a .csv file in an Amazon S3 bucket. The company must encrypt the data and must control which applications have access to the encryption key. Which solution will meet these requirements?

A. Create a new SSH access key and use the AWS Encryption CLI to encrypt the file.
 B. Create a new API key by using Amazon API Gateway and use it to encrypt the file. 
C. Create a new IAM role with permissions for kms:GenerateDataKey and use the role to encrypt the file. 
D. Create a new AWS Key Management Service (AWS KMS) key and use the AWS Encryption CLI with the KMS key to encrypt the file. 

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Question # 74

A company has an ML model that generates text descriptions based on images that customers upload to the company's website. The images can be up to 50 MB in total size. An ML engineer decides to store the images in an Amazon S3 bucket. The ML engineer must implement a processing solution that can scale to accommodate changes in demand. Which solution will meet these requirements with the LEAST operational overhead?

A. Create an Amazon SageMaker batch transform job to process all the images in the S3 bucket. 
B. Create an Amazon SageMaker Asynchronous Inference endpoint and a scaling policy. Run a script to make an inference request for each image. 
C. Create an Amazon Elastic Kubernetes Service (Amazon EKS) cluster that uses Karpenter for auto scaling. Host the model on the EKS cluster. Run a script to make an inference request for each image. 
D. Create an AWS Batch job that uses an Amazon Elastic Container Service (Amazon ECS) cluster. Specify a list of images to process for each AWS Batch job. 

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Question # 75

A company wants to deploy an Amazon SageMaker AI model that can queue requests. The model needs to handle payloads of up to 1 GB that take up to 1 hour to process. The model must return an inference for each request. The model also must scale down when no requests are available to process. Which inference option will meet these requirements?

A. Asynchronous inference 
B. Batch transform 
C. Serverless inference 
D. Real-time inference 

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Question # 76

A company has deployed an ML model that detects fraudulent credit card transactions in real time in a banking application. The model uses Amazon SageMaker Asynchronous Inference. Consumers are reporting delays in receiving the inference results. An ML engineer needs to implement a solution to improve the inference performance. The solution also must provide a notification when a deviation in model quality occurs. Which solution will meet these requirements?

A. Use SageMaker real-time inference for inference. Use SageMaker Model Monitor for notifications about model quality. 
B. Use SageMaker batch transform for inference. Use SageMaker Model Monitor for notifications about model quality. 
C. Use SageMaker Serverless Inference for inference. Use SageMaker Inference Recommender for notifications about model quality. 
D. Keep using SageMaker Asynchronous Inference for inference. Use SageMaker Inference Recommender for notifications about model quality. 

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Question # 77

An ML engineer is using Amazon Quick Suite (previously known as Amazon QuickSight) anomaly detection to detect very high or very low machine operating temperatures compared to normal. The ML engineer sets the Severity parameter to Low and above. The ML engineer sets the Direction parameter to All. What effect will the ML engineer observe in the anomaly detection results if the ML engineer changes the Direction parameter to Lower than expected?

A. Increased anomaly identification frequency and increased recall 
B. Decreased anomaly identification frequency and decreased recall 
C. Increased anomaly identification frequency and decreased recall 
D. Decreased anomaly identification frequency and increased recall 

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Question # 78

An ML engineer decides to use Amazon SageMaker AI automated model tuning (AMT) for hyperparameter optimization (HPO). The ML engineer requires a tuning strategy that uses regression to slowly and sequentially select the next set of hyperparameters based on previous runs. The strategy must work across small hyperparameter ranges. Which solution will meet these requirements?

A. Grid search 
B. Random search 
C. Bayesian optimization 
D. Hyperband 

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Question # 79

A company has an application that uses different APIs to generate embeddings for input text. The company needs to implement a solution to automatically rotate the API tokens every 3 months. Which solution will meet this requirement?

A. Store the tokens in AWS Secrets Manager. Create an AWS Lambda function to perform the rotation. 
B. Store the tokens in AWS Systems Manager Parameter Store. Create an AWS Lambda function to perform the rotation. 
C. Store the tokens in AWS Key Management Service (AWS KMS). Use an AWS managed key to perform the rotation. 
D. Store the tokens in AWS Key Management Service (AWS KMS). Use an AWS owned key to perform the rotation. 

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Question # 80

An ML engineer needs to organize a large set of text documents into topics. The ML engineer will not know what the topics are in advance. The ML engineer wants to use builtin algorithms or pre-trained models available through Amazon SageMaker AI to process the documents. Which solution will meet these requirements?

A. Use the BlazingText algorithm to identify the relevant text and to create a set of topics based on the documents. 
B. Use the Sequence-to-Sequence algorithm to summarize the text and to create a set of topics based on the documents. 
C. Use the Object2Vec algorithm to create embeddings and to create a set of topics based on the embeddings. 
D. Use the Latent Dirichlet Allocation (LDA) algorithm to process the documents and to create a set of topics based on the documents. 

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