A financial services company has developed an AI model by using AWS. The AI model assists with reviewing customer loan applications. Because regulatory requirements require transparency, the company needs to be able to explain how the model makes its decisions.Which AWS service or feature meets these requirements?
Answer(s): A
Amazon SageMaker Clarify helps explain how machine learning models make predictions by providing model explainability and feature-attribution capabilities. This supports transparency and regulatory requirements for decisions such as loan application reviews.
A company wants to fine-tune an ML model that is hosted on Amazon Bedrock. The company wants to use its own sensitive data that is stored in private databases in a VPC. The data needs to stay within the company’s private network.Which solution will meet these requirements?
Answer(s): C
AWS PrivateLink enables secure, private connectivity between your VPC and Amazon Bedrock without exposing data to the public internet, ensuring that sensitive data stays within your private network during fine-tuning.
A retail store wants to predict the demand for a specific product for the next few weeks by using the AmazonSageMaker DeepAR forecasting algorithm.Which type of data will meet this requirement?
The Amazon SageMaker DeepAR forecasting algorithm is specifically designed for forecasting scalar(one-dimensional) time series data using recurrent neural networks (RNNs). It excels when trained on datasets containing hundreds of related time series, enabling it to learn patterns across multiple series and provide accurate forecasts.
https://docs.aws.amazon.com/sagemaker/latest/dg/deepar.html
A documentary filmmaker wants to reach more viewers. The filmmaker wants to automatically add subtitles and voice-overs in multiple languages to their films.Which combination of steps will meet these requirements? (Choose two.)
Answer(s): A,C
Use Amazon Transcribe and Amazon Translate to generate subtitles in other languages: Amazon Transcribe converts spoken dialogue to text (subtitles), and Amazon Translate can then translate these subtitles into multiple languages.Use Amazon Polly to generate voice-overs in other languages: Amazon Polly converts translated text into lifelike speech, enabling the creation of multilingual voice-overs.
Which phase of the ML lifecycle determines compliance and regulatory requirements?
The data collection phase of the ML lifecycle is the most relevant for determining compliance and regulatory requirements. During this phase, organizations must ensure that the data being collected and used for training the model complies with legal and regulatory standards, such as data privacy laws (e.g., GDPR, HIPAA),industry-specific regulations, and ethical considerations. The organization must also verify that they have the proper consent to use the data and that the data does not contain any biases or violate any regulations.
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