Properties (66)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
software
|
| gptkbp:allows |
Data preparation
Model tuning |
| gptkbp:developedBy |
gptkb:Amazon_Web_Services
|
| gptkbp:enables |
Model training
|
| gptkbp:facilitates |
Model deployment
|
| gptkbp:features |
Collaboration tools
|
| https://www.w3.org/2000/01/rdf-schema#label |
SageMaker Studio
|
| gptkbp:includes |
Built-in algorithms
|
| gptkbp:integratesWith |
AWS_services
|
| gptkbp:isAccessibleBy |
Web interface
|
| gptkbp:isAvailableIn |
gptkb:AWS_Marketplace
Researchers Students Startups Multiple regions Enterprise use |
| gptkbp:isCompatibleWith |
gptkb:PyTorch
TensorFlow Docker Scikit-learn |
| gptkbp:isIntegratedWith |
gptkb:Amazon_S3
gptkb:AWS_Lambda gptkb:Amazon_EC2 gptkb:Amazon_SageMaker_Pipelines gptkb:Amazon_SageMaker_Ground_Truth Amazon SageMaker Debugger Amazon SageMaker Model Monitor Amazon SageMaker Neo |
| gptkbp:isOptimizedFor |
Scalability
|
| gptkbp:isPartOf |
Cloud computing solutions
SageMaker suite AWS_AI_services |
| gptkbp:isUsedBy |
Data scientists
Machine learning engineers |
| gptkbp:isUsedFor |
Data science
Deep learning Natural language processing Computer vision Anomaly detection Predictive analytics Reinforcement learning Time series forecasting |
| gptkbp:offers |
Version control
Resource management Jupyter notebooks Experiment management Model monitoring |
| gptkbp:provides |
Documentation
User-friendly interface Real-time monitoring Security features Interactive development Cost management tools Data labeling Machine_Learning_tools |
| gptkbp:supports |
Python
R Data visualization Batch processing Containerized applications AutoML Multi-user environments Real-time inference Custom algorithms Model explainability |