Google Cloud AI Platform Prediction
GPTKB entity
Statements (63)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:cloud_services
|
| gptkbp:enables |
Scalable Predictions
|
| https://www.w3.org/2000/01/rdf-schema#label |
Google Cloud AI Platform Prediction
|
| gptkbp:integrates_with |
gptkb:Big_Query
gptkb:cloud_storage |
| gptkbp:is_available_for |
gptkb:enterprise_solutions
|
| gptkbp:is_available_in |
Multiple Regions
|
| gptkbp:is_compatible_with |
gptkb:Jupyter_Notebooks
|
| gptkbp:is_integrated_with |
gptkb:Google_Cloud_AI_Services
|
| gptkbp:is_part_of |
gptkb:Google_Cloud_Platform
AI and Machine Learning Services Cloud AI Ecosystem |
| gptkbp:is_used_by |
gptkb:developers
Data Scientists Machine Learning Engineers |
| gptkbp:is_used_for |
gptkb:Business_Intelligence
Predictive Modeling |
| gptkbp:offers |
Cost Management Tools
Model Monitoring Documentation and Tutorials Integration with Third-Party Tools Batch Prediction Model Evaluation Tools Online Prediction Versioning for Models Custom Container Support Integration with AI Hub Integration with Tensor Flow Extended (TFX) Model Training Services |
| gptkbp:provides |
Data Encryption
Scalability Collaboration Tools Logging and Monitoring Security Features Service Level Agreements (SLAs) User-Friendly Interface User Support Services User Access Controls Machine Learning Model Deployment Auto ML capabilities REST API for predictions |
| gptkbp:supports |
gptkb:XGBoost
gptkb:Tensor_Flow gptkb:Hyperparameter_Tuning gptkb:Android gptkb:Data_Analytics gptkb:Scikit-learn gptkb:A/_B_Testing Data Preprocessing Feature Engineering Multi-Region Deployment Data Versioning Data Science Workflows Real-time Predictions Model Serving Model Retraining Python SDK Go SDK Custom Prediction Routines Containerized Models |
| gptkbp:uses |
gptkb:Kubernetes
|
| gptkbp:bfsParent |
gptkb:Google
|
| gptkbp:bfsLayer |
4
|