Google Cloud AI Platform Pipelines

URI: https://gptkb.org/entity/Google_Cloud_AI_Platform_Pipelines
GPTKB entity
Statements (64)
Predicate Object
gptkbp:instance_of gptkb:AI_technology
gptkbp:allows pipeline orchestration
gptkbp:developed_by gptkb:Google
gptkbp:enables automated model training
collaborative model development
gptkbp:facilitates model deployment
https://www.w3.org/2000/01/rdf-schema#label Google Cloud AI Platform Pipelines
gptkbp:integrates_with Google Cloud services
gptkbp:is_accessible_by gptkb:Google_Cloud_Console
REST API
gcloud command line tool
gptkbp:is_available_for individual developers
enterprise users
gptkbp:is_available_in multiple regions
gptkbp:is_compatible_with gptkb:XGBoost
gptkb:Tensor_Flow
gptkb:scikit-learn
gptkb:Py_Torch
gptkbp:is_documented_in Google Cloud documentation
gptkbp:is_integrated_with gptkb:Big_Query
gptkb:Cloud_Functions
gptkb:cloud_storage
gptkbp:is_optimized_for gptkb:performance
gptkbp:is_part_of gptkb:Google_Cloud_Platform
Google Cloud AI ecosystem
cloud-native solutions
Google Cloud AI and ML services
gptkbp:is_scalable large datasets
gptkbp:is_supported_by community forums
tutorials and guides
Google support
gptkbp:is_used_by data scientists
machine learning engineers
gptkbp:is_used_for data preprocessing
data science projects
model evaluation
feature engineering
real-time predictions
model monitoring
model retraining
batch predictions
production ML systems
gptkbp:offers security features
visualization tools
experiment tracking
gptkbp:provides data lineage tracking
monitoring capabilities
user-friendly interface
automated testing
end-to-end machine learning workflows
reproducibility of experiments
version control for models
gptkbp:supports gptkb:Kubeflow_Pipelines
custom components
data validation
hyperparameter tuning
data augmentation
ensemble methods
multi-cloud deployments
A/ B testing
CI/ CD for ML models
gptkbp:utilizes Docker containers
gptkbp:bfsParent gptkb:Google
gptkbp:bfsLayer 4