A company that uses multiple ML models wants to identify changes in original model quality so that the company can resolve any issues.Which AWS service or feature meets these requirements?
Answer(s): D
SageMaker Model Monitor continuously measures data and prediction quality in production, detects deviations from your model’s baseline (such as data drift or accuracy degradation), and alerts you so you can investigate and resolve issues promptly.
A company wants to create a new solution by using AWS Glue. The company has minimal programming experience with AWS Glue.Which AWS service can help the company use AWS Glue?
Answer(s): A
Amazon Q Developer is a tool designed to help users with minimal programming experience to work with AWSGlue. It provides a graphical user interface and simplifies the creation of data transformation and extraction workflows, allowing users to perform tasks like querying and working with data without needing deep coding skills.
HOTSPOT (Drag and Drop is not supported)A company wants to develop a solution that uses generative AI to create content for product advertisements,including sample images and slogans.Select the correct model type from the following list for each action. Each model type should be selected one time.Hot Area:
Create high-quality images that are influenced by the generated slogans and product -> Diffusion modelCreate contextually relevant slogans based on the advertisement product -> Transformer-based modelEnsure that company brand elements are properly placed in the images -> Object detection modelDiffusion models are state-of-the-art for high-quality image generation.Transformer-based models excel at natural language processing, making them suitable for generating contextually relevant slogans.Object detection models are designed to identify and ensure correct placement of specific objects (e.g., brand elements) within images.
Which option describes embeddings in the context of AI?
Embeddings are numerical representations of data, such as words, images, or items, in a lower-dimensional vector space. They capture semantic relationships and patterns in the data, enabling models to process and compare inputs efficiently.
Which functionality does Amazon SageMaker Clarify provide?
Amazon SageMaker Clarify helps detect potential bias in datasets and models during data preparation,training, and deployment. It also provides tools for explainability. The other options are functionalities that do not directly match SageMaker Clarify's core features.
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