Microsoft Azure Machine Learning
GPTKB entity
Statements (69)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:cloud_services
|
| gptkbp:developed_by |
gptkb:Microsoft
|
| https://www.w3.org/2000/01/rdf-schema#label |
Microsoft Azure Machine Learning
|
| gptkbp:includes |
data preparation tools
model deployment tools model training tools |
| gptkbp:integrates_with |
gptkb:Azure_Databricks
gptkb:Power_BI gptkb:Azure_Dev_Ops |
| gptkbp:offers |
gptkb:machine_learning
compliance certifications data visualization tools hyperparameter tuning data storage solutions collaboration features performance optimization tools cost management tools user training programs learning resources data labeling services batch inferencing data science competitions real-time inferencing API management features data exploration tools custom model deployment model monitoring capabilities data pipeline automation |
| gptkbp:provides |
community support
feedback mechanisms scalability options security features user-friendly interface machine learning capabilities model evaluation tools model versioning user management features experiment tracking SDKs for various languages business intelligence integration model management capabilities training on large datasets visual interface for model building integration with Azure services AI model explainability tools notebooks for development |
| gptkbp:supports |
gptkb:Kubernetes
gptkb:Tensor_Flow gptkb:Python gptkb:R gptkb:scikit-learn gptkb:Py_Torch gptkb:MLflow gptkb:Jupyter_notebooks Docker containers REST APIs cloud-native applications data governance data privacy regulations multi-cloud environments real-time analytics collaborative projects feature engineering data ingestion tools open-source frameworks data science workflows AI ethics guidelines |
| gptkbp:bfsParent |
gptkb:Microsoft
|
| gptkbp:bfsLayer |
4
|