Statements (68)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:software_framework
|
| gptkbp:bfsLayer |
4
|
| gptkbp:bfsParent |
gptkb:Microsoft_cloud_services
|
| gptkbp:developed_by |
gptkb:Microsoft
|
| gptkbp:enables |
Collaboration among data scientists
|
| https://www.w3.org/2000/01/rdf-schema#label |
Azure ML Studio
|
| gptkbp:integrates_with |
gptkb:Azure_Data_Lake
gptkb:Azure_SQL_Database gptkb:Azure_Databricks |
| gptkbp:offers |
Security features
Hyperparameter tuning Collaboration features Experiment tracking Scalability for large datasets Integration with Azure Functions Integration with Azure Logic Apps Integration with Azure Monitor Integration with Power BI Visual interface for model building Automated machine learning Integration with Git Hub Integration with Azure Dev Ops Integration with Azure Active Directory Integration with Azure Kubernetes Service Integration with Azure Batch |
| gptkbp:provides |
Data labeling services
Pre-built algorithms Documentation and tutorials Access to community resources Data preparation tools Model training capabilities Experiment management Access to Azure Marketplace Model deployment services Access to training datasets Access to pre-trained models Access to Azure Cognitive Services Access to cloud storage solutions Access to compute instances Access to machine learning competitions |
| gptkbp:released |
gptkb:2018
|
| gptkbp:supports |
gptkb:Jupyter_Notebooks
gptkb:R gptkb:Library Containerization Multi-language support Data governance features Data transformation capabilities Data visualization tools Real-time scoring Data preprocessing tools Model evaluation metrics Version control for models Data import from various sources Custom visualizations Data quality assessment tools Data science workflows Experiment reproducibility Model lifecycle management Model monitoring Data enrichment capabilities Model explainability tools Model retraining capabilities Batch scoring Custom model development Deployment to edge devices Model performance optimization |
| gptkbp:uses |
Cloud computing resources
|