1. ML LifeCycle 구성요소
* Data Collection and Preparation
* Feature Engineering
* Model Selection and Model Learning
* Model Evaluation and Model Tuning
* Deployment and Monitoring
* Re Evaluation and Model Update
2. 문제들
MLOps Orchestrator (0) | 2024.01.04 |
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MLOps인프라와 도구 (Container) (0) | 2024.01.03 |
iterrows를 활용한 빈 리스트에 결과값 채워넣기 (1) | 2023.12.07 |
Graph Data Model - AWS Neptune Graph DB (0) | 2023.12.06 |
Data Prep (Class Imbalance) (1) | 2023.12.06 |