Statements (51)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:AI_technology
|
| gptkbp:allows |
automatic feature engineering
|
| gptkbp:can_be_used_for |
real-time predictions
|
| gptkbp:can_be_used_to |
business analysts
data scientists |
| gptkbp:can_create |
multiple model candidates
explainable AI reports |
| gptkbp:can_handle |
tabular data
|
| gptkbp:deployment |
machine learning models
|
| gptkbp:developed_by |
gptkb:Amazon_Web_Services
|
| https://www.w3.org/2000/01/rdf-schema#label |
Amazon Sage Maker Autopilot
|
| gptkbp:integrates_with |
gptkb:Amazon_Redshift
gptkb:Amazon_S3 gptkb:AWS_Lambda gptkb:Sage |
| gptkbp:is_accessible_by |
gptkb:AWS_Management_Console
command line interface |
| gptkbp:is_available_in |
multiple AWS regions
|
| gptkbp:is_compatible_with |
gptkb:Python
gptkb:R |
| gptkbp:is_effective_against |
yes
|
| gptkbp:is_enhanced_by |
machine learning algorithms
|
| gptkbp:is_optimized_for |
AWS infrastructure
|
| gptkbp:is_part_of |
AWS ecosystem
AWS AI services Amazon Sage Maker suite |
| gptkbp:is_scalable |
gptkb:cloud_services
|
| gptkbp:is_supported_by |
AWS documentation
|
| gptkbp:is_updated_by |
yes
|
| gptkbp:is_used_for |
predictive analytics
|
| gptkbp:is_used_in |
various industries
|
| gptkbp:is_user_friendly |
yes
|
| gptkbp:offers |
API access
data visualization tools Jupyter notebook integration |
| gptkbp:provides |
hyperparameter optimization
automated machine learning capabilities model performance metrics model explainability data labeling capabilities model selection capabilities |
| gptkbp:suitable_for |
small to large datasets
|
| gptkbp:supports |
data preprocessing
classification tasks model evaluation ensemble methods time series forecasting model training regression tasks |
| gptkbp:bfsParent |
gptkb:AWS
|
| gptkbp:bfsLayer |
4
|