HOTSPOT
An ML engineer is building a generative AI application on Amazon Bedrock by using large language models (LLMs).
Select the correct generative AI term from the following list for each description. Each term should be selected one time or not at all. (Select three.)
• Embedding
• Retrieval Augmented Generation (RAG)
• Temperature
• Token

Solution:


Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

Case study
An ML engineer is developing a fraud detection model on AWS. The training dataset includes transaction logs, customer profiles, and tables from an on-premises MySQL database. The transaction logs and customer profiles are stored in Amazon S3.
The dataset has a class imbalance that affects the learning of the model's algorithm. Additionally, many of the features have interdependencies. The algorithm is not capturing all the desired underlying patterns in the data.
After the data is aggregated, the ML engineer must implement a solution to automatically detect anomalies in the data and to visualize the result.
Which solution will meet these requirements?

1. A. Use Amazon Athena to automatically detect the anomalies and to visualize the result.
2. B. Use Amazon Redshift Spectrum to automatically detect the anomalie
3. C. Use Amazon QuickSight to visualize the result.
4. D. Use Amazon SageMaker Data Wrangler to automatically detect the anomalies and to visualize the result.
5. E. Use AWS Batch to automatically detect the anomalie
6. F. Use Amazon QuickSight to visualize the result.

Correct Answer: C

HOTSPOT
An ML engineer is working on an ML model to predict the prices of similarly sized homes. The model will base predictions on several features The ML engineer will use the following feature engineering techniques to estimate the prices of the homes:
• Feature splitting
• Logarithmic transformation
• One-hot encoding
• Standardized distribution
Select the correct feature engineering techniques for the following list of features. Each feature engineering technique should be selected one time or not at all (Select three.)

Solution:


Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

A company is using Amazon SageMaker and millions of files to train an ML model. Each file is several megabytes in size. The files are stored in an Amazon S3 bucket. The company needs to improve training performance.
Which solution will meet these requirements in the LEAST amount of time?

1. A. Transfer the data to a new S3 bucket that provides S3 Express One Zone storag
2. B. Adjust the training job to use the new S3 bucket.
3. C. Create an Amazon FSx for Lustre file syste
4. D. Link the file system to the existing S3 bucke
5. E. Adjust the training job to read from the file system.
6. F. Create an Amazon Elastic File System (Amazon EFS) file syste
7. G. Transfer the existing data to the file syste
8. H. Adjust the training job to read from the file system.
9. I. Create an Amazon ElastiCache (Redis OSS) cluste
10. J. Link the Redis OSS cluster to the existing S3 bucke
11. K. Stream the data from the Redis OSS cluster directly to the training job.

Correct Answer: B

A company is planning to use Amazon Redshift ML in its primary AWS account. The source data is in an Amazon S3 bucket in a secondary account.
An ML engineer needs to set up an ML pipeline in the primary account to access the S3 bucket in the secondary account. The solution must not require public IPv4 addresses.
Which solution will meet these requirements?

1. A. Provision a Redshift cluster and Amazon SageMaker Studio in a VPC with no public access enabled in the primary accoun
2. B. Create a VPC peering connection between the account
3. C. Update the VPC route tables to remove the route to 0.0.0.0/0.
4. D. Provision a Redshift cluster and Amazon SageMaker Studio in a VPC with no public access enabled in the primary accoun
5. E. Create an AWS Direct Connect connection and a transit gatewa
6. F. Associate the VPCs from both accounts with the transit gatewa
7. G. Update the VPC route tables to remove the route to 0.0.0.0/0.
8. H. Provision a Redshift cluster and Amazon SageMaker Studio in a VPC in the primary accoun
9. I. Create an AWS Site-to-Site VPN connection with two encrypted IPsec tunnels between the account
10. J. Set up interface VPC endpoints for Amazon S3.
11. K. Provision a Redshift cluster and Amazon SageMaker Studio in a VPC in the primary accoun
12. L. Create an S3 gateway endpoin
13. M. Update the S3 bucket policy to allow IAM principals from the primary accoun
14. N. Set up interface VPC endpoints for SageMaker and Amazon Redshift.

Correct Answer: D