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Subscribe如何從DevOps團隊，轉換到MLOps團隊。 - 蔡効謙
歡迎來到 DevOpsDay Taipei 2022 共筆
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Learn More →共筆入口：https://hackmd.io/@DevOpsDay/2022
手機版請點選上方 按鈕展開議程列表。
tags:
DevOpsDays Taipei 2022repo: https://github.com/HCTsai/MLOps_DevOpsDays_2022
DevOps 降低開發成本
MLOps 將低開發AI成本
ML 與 DevOps 的盲點
實施DevOps 把AI功能當作一個功能 （不建議）
導入CI/CD將AI模型當一份檔案 （不建議）
套用MLOps工具不是MLOps的目的
從Data Training Deploy 三個層面思考團隊現的的目標困難與未來挑戰
MLFlow
ML實驗過程：透明、公開、可回朔結果、可互相討論學習
統一紀錄與管理實驗產生的數據及，特徵資料、模型、表現
只要改寫Loggin方式，就能夠完整紀錄實驗過程到雲端
ML資料與模型儲存
MinIO > 多版本的Object Storage
Continuous Training / Continuous Monitoring
用AI來監控AI，將特殊資料自動標記，減少人工標注的工作，隨時提升資料品質
CT除了定時重新訓練模型以外，還要有動態提升資料品質的機制
GitHub: https://github.com/HCTsai/MLOps_DevOpsDays_2022