Statements (61)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:machine_learning
|
| gptkbp:developed_by |
gptkb:Google
|
| gptkbp:has |
gptkb:user_interface
gptkb:Community_Support |
| gptkbp:has_feature |
gptkb:Apache_Hive
gptkb:Identity_and_Access_Management Batch Processing CLI Tools Monitoring and Logging Real-time Inference Security Features Visualization Tools Artifact Management Custom Resource Definitions Web UI Pipeline Management Experiment Tracking Integration with Jupyter Notebooks Support for GPUs Support for Reinforcement Learning Support for Canary Releases Support for Model Deployment Integration with CI/ CD Tools Support for A/ B Testing Multi-Framework Support Support for Auto ML Support for Blue/ Green Deployments Support for Data Preprocessing Support for Distributed Training Support for Feature Engineering Support for Model Evaluation Support for Monitoring Models Support for TPUs |
| https://www.w3.org/2000/01/rdf-schema#label |
Kube Flow
|
| gptkbp:includes |
gptkb:Pipeline
gptkb:KFServing Katib Training Operators |
| gptkbp:is |
gptkb:Open_Source
Portable Scalable Extensible Cloud Native |
| gptkbp:is_compatible_with |
gptkb:AWS
gptkb:GCP gptkb:Azure On-Premises |
| gptkbp:is_used_by |
Data Scientists
Machine Learning Engineers Dev Ops Engineers |
| gptkbp:offers |
Model Serving
|
| gptkbp:provides |
gptkb:Hyperparameter_Tuning
Distributed Training Machine Learning Pipelines |
| gptkbp:supports |
gptkb:Tensor_Flow
gptkb:MXNet gptkb:Py_Torch |
| gptkbp:uses |
gptkb:Kubernetes
|
| gptkbp:written_in |
gptkb:Go
|
| gptkbp:bfsParent |
gptkb:CNCF
|
| gptkbp:bfsLayer |
5
|