Google Cloud AI Platform Model Registry

GPTKB entity

Statements (73)
Predicate Object
gptkbp:instance_of gptkb:archaeological_site
gptkbp:bfsLayer 3
gptkbp:bfsParent gptkb:Job_Search_Engine
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_Computing_Service
Google Cloud services
gptkbp:is_accessible_by RESTAPI
gcloud command line tool
gptkbp:is_compatible_with gptkb:lake
gptkb:fortification
gptkb:Jupyter_Notebooks
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: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
batch predictions
model explainability
model serving
Tensor Flow models
XG Boost models
scikit-learn models
gptkbp:user_experience gptkb:software
data scientists
data engineers