AWS AWS Machine Learning and AI Services 4

Question 1

Which AWS service provides a fully managed Jupyter notebook environment for data scientists to build and train ML models?

Accepted Answer

Amazon SageMaker Studio

Answer

Amazon SageMaker Studio is a fully managed, web-based IDE that provides Jupyter notebooks along with tools for building, training, and deploying ML models.

Question 2

What does Amazon Rekognition Custom Labels allow you to do?

Accepted Answer

Train a custom image classification model using your own labeled images

Answer

Amazon Rekognition Custom Labels lets you train a custom computer vision model using your own labeled dataset without deep ML expertise.

Question 3

An ML team wants to detect data drift in a deployed SageMaker model. Which SageMaker feature should they enable?

Accepted Answer

SageMaker Model Monitor

Answer

SageMaker Model Monitor continuously monitors deployed models for data quality drift, model quality drift, and bias drift.

Question 4

Which AWS AI service can automatically extract text, forms, and tables from scanned documents?

Accepted Answer

Amazon Textract

Answer

Amazon Textract uses ML to automatically extract printed text, handwriting, forms, and tables from documents without manual configuration.

Question 5

What is the purpose of SageMaker Feature Store?

Accepted Answer

A centralized repository to store, share, and retrieve ML features for training and inference

Answer

SageMaker Feature Store provides a centralized store for ML features, enabling consistent feature definitions across training and real-time inference.

AWS Practice Test

AWS Practice Test

AWS AWS Machine Learning and AI Services 4