Kubeflow

GPTKB entity

Statements (95)
Predicate Object
gptkbp:instance_of gptkb:software_framework
gptkbp:bfsLayer 3
gptkbp:bfsParent gptkb:fortification
gptkbp:constructed_in Containerization
gptkbp:developed_by gptkb:Job_Search_Engine
gptkbp:game_components gptkb:Kubeflow_Pipelines
Metadata Store
Katib
Training Operators
Central Dashboard
KF Serving
Notebook Servers
Pipeline UI
gptkbp:has_community gptkb:Kubeflow_Community
gptkb:software_framework
gptkbp:has_documentation Official Documentation
gptkbp:has_feature gptkb:Company
gptkb:operating_system
CLI Tools
RESTAPI
gptkbp:hosted_by gptkb:archive
https://www.w3.org/2000/01/rdf-schema#label Kubeflow
gptkbp:includes gptkb:Pipeline
gptkb:Kubeflow_Pipelines
Katib
Training Operators
KF Serving
KF Serving for model serving
Katib for hyperparameter tuning
gptkbp:integrates_with gptkb:Jupyter_Notebooks
gptkb:Prometheus
gptkb:opera
gptkb:board_game
gptkb:Argo_Workflows
gptkbp:is_adopted_by gptkb:Educational_Institution
Enterprises
Research Institutions
Startups
gptkbp:is_available_on gptkb:Docker_Hub
gptkb:archive
gptkbp:is_compatible_with Cloud Providers
On-Premises Deployments
CI/ CD Tools
gptkbp:is_designed_for Machine Learning Workflows
End-to-End ML Workflows
gptkbp:is_open_source gptkb:theorem
gptkbp:is_optimized_for gptkb:collaboration
Scalability
Reproducibility
gptkbp:is_part_of gptkb:Cloud_Native_Computing_Foundation
Cloud Native Ecosystem
AI/ ML Ecosystem
gptkbp:is_promoted_by gptkb:Cloud_Native_Community
gptkb:Cloud_Native_Computing_Foundation
Machine Learning Community
Kubernetes Community
gptkbp:is_scalable gptkb:theorem
gptkbp:is_supported_by gptkb:software_framework
Community Contributions
Corporate Sponsorships
Cloud Providers
gptkbp:is_used_by Data Scientists
Machine Learning Engineers
gptkbp:is_used_for gptkb:Company
Model Evaluation
Model Training
Feature Engineering
Model Deployment
Data Preparation
gptkbp:latest_version 1.5.0
gptkbp:license Apache License 2.0
gptkbp:notable_recipients Open Source Contributors
gptkbp:provides gptkb:software
Machine Learning Pipelines
Model Serving
Experiment Tracking
Pipeline for ML workflows
gptkbp:release_date gptkb:2017
gptkbp:released Regular Releases
gptkbp:supports gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
Multi-Cloud Deployments
MX Net
On-Premise Deployments
gptkbp:tutorials Online Tutorials
gptkbp:use_case gptkb:software
Model Evaluation
Model Training
Deployment Automation
Monitoring and Logging
Data Preparation
Model Serving
Experiment Tracking
gptkbp:uses gptkb:fortification
gptkbp:written_in gptkb:Go