- Definition
- Initial AI/ML workflow implementation for O-RAN environment. Need to interact with another project to accomplish a whole life cycle management of the AI model.
- Project Scope
- AI 모델 라이프 사이클 관리 ( 모델 학습 파이프라인 관리 / 학습완료된 모델 버전 관리 및 배포시스템 연동 / AI 서비스 (Application) 관리 ) , Dashboard
- AI 모델 학습 환경 ( 데이터 추출 / Feature 관리 및 연동 / AI 모델 저장 기능 / 모델 학습 플랫폼 지원 or 모델 학습/학습 파이프라인 구동 환경 )
- AI 모델 추론 환경 ( 모델 서빙 플랫폼 지원 or 모델 추론 서비스 구동 환경 )
- g rel scope
AIML Framework (AIMLFW)
Mission: Stand-alone installation (separated from existing platform deployment) and initial AIML workflow modules
Original primary goals:
• Stand-alone installation with Kubeflow as a Training host backend and Kserve as a Inference host backend
• Manual Deployment of ML rApp and ML xApp
• Training Job Management: Create/Edit/Delete usecases and Training pipelines and monitoring current training jobs
• Data Extraction for model training from data lake
• Model feature database for Training pipeline
• Trained model storage
• Sample ML pipeline and ML xApp : QoE Prediction model using LSTM with data from ricapp/qp
G release source code, container images and deployment instructions
TODO