AWS AI Practitioner 5 - SageMaker

Question 1

Amazon SageMaker

Answer 1

Fully managed service for developers and data scientists to build; train; and deploy machine learning models

Question 2

Automatic Model Tuning

Answer 2

Feature in SageMaker that automatically tunes hyperparameters to optimize model performance

Question 3

SageMaker Studio

Answer 3

Unified interface for end-to-end machine learning development in SageMaker

Question 4

Data Wrangler

Answer 4

SageMaker tool for preparing; transforming; and exploring data for machine learning

Question 5

Feature Store

Answer 5

Central repository in SageMaker for storing and managing machine learning features

Question 6

SageMaker Clarify

Answer 6

Tool for evaluating foundation models; explaining model predictions; and detecting bias

Question 7

Ground Truth

Answer 7

SageMaker feature for reinforcement learning from human feedback and data labeling

Question 8

Model Cards

Answer 8

Documentation tool in SageMaker for gathering essential model information

Question 9

Model Dashboard

Answer 9

Centralized repository in SageMaker for viewing all machine learning models

Question 10

Role Manager

Answer 10

SageMaker tool for defining permissions and roles for different personas

Question 11

Model Monitor

Answer 11

SageMaker feature for tracking model quality and alerting on deviations

Question 12

Model Registry

Answer 12

Centralized repository in SageMaker for tracking and versioning machine learning models

Question 13

SageMaker Pipelines

Answer 13

Workflow tool for automating the process of building; training; and deploying ML models

Question 14

JumpStart

Answer 14

Machine learning hub in SageMaker for finding pre-trained models and solutions

Question 15

SageMaker Canvas

Answer 15

No-code visual interface in SageMaker for building machine learning models

Question 16

MLFlow

Answer 16

Open-source tool integrated with SageMaker for managing the machine learning lifecycle