Google Cloud AI Platform Model Registry
GPTKB entity
Statements (73)
Predicate | Object |
---|---|
gptkbp:instance_of |
gptkb:Apache_Hive
|
gptkbp:allows |
model deployment
model sharing model metadata management |
gptkbp:enables |
collaboration among teams
model deployment automated model deployment model lifecycle management |
gptkbp:facilitates |
model monitoring
collaboration among data scientists |
https://www.w3.org/2000/01/rdf-schema#label |
Google Cloud AI Platform Model Registry
|
gptkbp:integrates_with |
gptkb:cloud_storage
Google Cloud services |
gptkbp:is_accessible_by |
REST API
gcloud command line tool |
gptkbp:is_compatible_with |
gptkb:Kubernetes
gptkb:Jupyter_Notebooks gptkb:Docker Colab |
gptkbp:is_integrated_with |
gptkb:AI_Platform_Prediction
gptkb:Big_Query gptkb:Cloud_Functions gptkb:Dataproc gptkb:Cloud_Run Cloud Monitoring Dataflow Cloud Logging AI Platform Training |
gptkbp:is_optimized_for |
cloud environments
AI workloads |
gptkbp:is_part_of |
gptkb:Google_AI_services
Google Cloud ecosystem AI and machine learning ecosystem |
gptkbp:is_scalable |
large datasets
|
gptkbp:is_used_by |
data scientists
|
gptkbp:is_used_for |
model evaluation
model optimization model governance model lifecycle management model performance tracking model retraining model deployment automation |
gptkbp:is_user_friendly |
gptkb:developers
data scientists data engineers |
gptkbp:offers |
API access
model monitoring model metadata management |
gptkbp:part_of |
gptkb:Google_Cloud_AI_Platform
|
gptkbp:provides |
API access
audit logs data visualization tools security features model evaluation tools model versioning user access controls version control for models model lineage tracking |
gptkbp:supports |
automated testing
custom model training real-time predictions machine learning models data versioning multiple frameworks multi-cloud deployments XGBoost models batch predictions model explainability model serving Tensor Flow models scikit-learn models |
gptkbp:bfsParent |
gptkb:Google
|
gptkbp:bfsLayer |
4
|