|
gptkbp:instanceOf
|
gptkb:cloud-based_machine_learning_platform
|
|
gptkbp:developedBy
|
gptkb:Microsoft
|
|
gptkbp:hasFeature
|
gptkb:REST_API
gptkb:collaboration
gptkb:model
endpoint management
security and compliance
monitoring
role-based access control
CLI
model versioning
SDK
compute management
data drift detection
integration with Visual Studio Code
integration with Jupyter Notebooks
drag-and-drop designer
explainability
responsible AI tools
|
|
gptkbp:integratesWith
|
gptkb:GitHub
gptkb:TensorFlow
gptkb:Azure_Container_Instances
gptkb:Azure_Kubernetes_Service
gptkb:Power_BI
gptkb:Azure_Data_Lake
gptkb:Azure_Synapse_Analytics
gptkb:PyTorch
gptkb:scikit-learn
gptkb:Azure_Blob_Storage
gptkb:ONNX
gptkb:Azure_DevOps
gptkb:MLflow
|
|
gptkbp:launched
|
2015
|
|
gptkbp:officialWebsite
|
https://azure.microsoft.com/en-us/services/machine-learning/
|
|
gptkbp:partOf
|
gptkb:Microsoft_Azure
|
|
gptkbp:providesService
|
data storage
hyperparameter tuning
data labeling
model deployment
pipelines
automated machine learning
experiment tracking
model management
model training
notebook compute
|
|
gptkbp:supportsLanguage
|
gptkb:Python
R
|
|
gptkbp:usedFor
|
gptkb:MLOps
data science
machine learning lifecycle management
AI model deployment
|
|
gptkbp:bfsParent
|
gptkb:Databricks_MLflow
|
|
gptkbp:bfsLayer
|
6
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Azure ML
|