Amazon SageMaker Model Registry
GPTKB entity
Properties (62)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Model Registry
|
| gptkbp:allows |
model deployment
|
| gptkbp:distributor |
model metadata
|
| gptkbp:enables |
team collaboration
model validation model experimentation model rollback automated model promotion model_discovery |
| gptkbp:facilitates |
model sharing
collaboration among data scientists |
| https://www.w3.org/2000/01/rdf-schema#label |
Amazon SageMaker Model Registry
|
| gptkbp:integratesWith |
AWS_services
|
| gptkbp:integration |
CI/CD pipelines
|
| gptkbp:isAccessibleBy |
gptkb:AWS_Management_Console
gptkb:SageMaker_Studio API_calls |
| gptkbp:isCompatibleWith |
Docker containers
Jupyter notebooks SageMaker_Pipelines |
| gptkbp:isDesignedFor |
enterprise use
|
| gptkbp:isDocumentedIn |
AWS documentation
AWS_blogs AWS_whitepapers |
| gptkbp:isIntegratedWith |
gptkb:Amazon_CloudWatch
gptkb:Amazon_S3 gptkb:AWS_Lambda |
| gptkbp:isOptimizedFor |
performance
scalability |
| gptkbp:isPartOf |
data-driven decision making
machine learning lifecycle AWS_ecosystem cloud-based_ML_solutions AI/ML_strategy |
| gptkbp:isRelatedTo |
machine learning models
|
| gptkbp:isSupportedBy |
AWS_SDKs
|
| gptkbp:isUsedBy |
data scientists
|
| gptkbp:isUsedFor |
model optimization
model lifecycle management |
| gptkbp:isUsedIn |
data science projects
production_ML_applications |
| gptkbp:isUtilizedFor |
business analysts
ML engineers |
| gptkbp:isUtilizedIn |
production environments
|
| gptkbp:offers |
model monitoring capabilities
|
| gptkbp:partOf |
Amazon SageMaker
|
| gptkbp:provides |
audit trails
model evaluation metrics model versioning model approval workflows model deployment options model metadata management model registration features |
| gptkbp:supports |
data preprocessing
A/B testing model testing data versioning model governance model performance tracking model retraining multiple model formats |
| gptkbp:track |
model lineage
|