Statements (75)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:AI_technology
|
| gptkbp:developed_by |
gptkb:Microsoft
|
| https://www.w3.org/2000/01/rdf-schema#label |
Azure Machine Learning
|
| gptkbp:integrates_with |
gptkb:Azure_Data_Lake_Storage
gptkb:Azure_Cognitive_Services gptkb:Azure_Synapse_Analytics gptkb:Azure_Databricks gptkb:Power_BI gptkb:Azure_Logic_Apps gptkb:Azure_Dev_Ops gptkb:Git_Hub gptkb:Azure_Event_Hubs |
| gptkbp:offers |
gptkb:machine_learning
collaboration tools community support data visualization tools hyperparameter tuning custom model training model serving capabilities model optimization tools data labeling services model deployment options real-time inferencing training on large datasets experiment automation AI model governance collaborative notebooks data science virtual machines pipeline orchestration |
| gptkbp:provides |
monitoring and logging capabilities
security features user-friendly interface data preparation tools model evaluation metrics model versioning user authentication features data ingestion tools experiment tracking notebooks for data analysis resource management tools batch inferencing AI insights model management capabilities scalable compute resources model interpretability tools visual interface for model building SDK for . NET cloud-based machine learning services cloud-based storage for models |
| gptkbp:supports |
gptkb:Kubernetes
gptkb:Tensor_Flow gptkb:Jupyter_Notebooks gptkb:Python gptkb:R gptkb:scikit-learn gptkb:Azure_Functions gptkb:Py_Torch gptkb:MLflow Docker containers REST APIs data analytics data governance feature engineering data exploration data pipelines data versioning multi-cloud deployments data science workflows data privacy features data connectors model retraining |
| gptkbp:bfsParent |
gptkb:Microsoft_Azure
gptkb:Microsoft gptkb:Azure |
| gptkbp:bfsLayer |
4
|