A financial company stores patterns of fraudulent behavior in a database. The company uses this data to conduct investigations.The company wants to use a graph-based ML solution to develop an AI tool that helps with these investigations.Which AWS service will meet these requirements?
Answer(s): C
Amazon Neptune is a fully managed graph database service designed for graph-based data models and graph analytics, making it suitable for building ML solutions that analyze relationships and patterns such as fraudulent behavior networks for investigation purposes.
A company wants to establish a data governance framework for its AI system. The framework must give the company the ability to monitor when data is generated, updated, and scheduled for deletion.Which data governance component meets these requirements?
Answer(s): B
Data lifecycle management defines and monitors how data is created, updated, retained, archived, and deleted. This supports governance by ensuring data is managed appropriately throughout its full lifecycle.
HOTSPOT (Drag and Drop is not supported)An ecommerce company is developing a generative AI solution to create personalized product recommendations for its application users. The company wants to track how effectively the AI solution increases product sales and user engagement in the application.Select the correct business metric from the following list for each business goal. Each business metric should be selected one time.Hot Area:
Answer(s): A
Measure how engaging the product recommendations are to users -> Click-through rate (CTR)Determine the effect of the AI solution on the total value of user purchases -> Average order value (AOV)Assess the AI solution's ability to encourage users to return to the platform -> Retention rateCTR reflects engagement with recommendations.AOV measures the impact on purchase value.Retention rate evaluates if users are returning due to the AI solution.
An AI practitioner is using an Amazon Bedrock foundation model (FM) to generate summaries of long research articles. The AI practitioner wants to compare the generated summaries with human-written summaries to see how closely the summaries match.Which metric will meet these requirements?
ROUGE evaluates the similarity between a generated summary and a reference summary by measuring overlap in words, phrases, or sequences. It is widely used for summarization tasks to determine how closely machine-generated summaries match human-written reference summaries.
A human resources company is building an AI/ML solution to screen resumes and select relevant applicants for various job roles.Which AI methodologies will help ensure impartial treatment for all demographic groups? (Choose two.)
Answer(s): B,C
Fairness helps ensure that the AI/ML solution treats demographic groups impartially and avoids biased outcomes. Explainability helps stakeholders understand how the model makes screening decisions, which supports transparency, accountability, and bias detection in a high-impact hiring use case.
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