[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-模型維運":3},{"tag":4,"articles":9},{"id":5,"name":6,"slug":6,"article_count":7,"description_zh":8,"description_en":8},"ffdc12af-e09a-4229-9ed5-2a17f39bbeb8","模型維運",0,null,[10],{"id":11,"slug":12,"title":13,"summary":14,"category":15,"image_url":16,"cover_image":16,"language":17,"created_at":18},"235397ea-a41f-4ff0-aaea-fcad743e2316","microsoft-mlops-maturity-model-five-levels-zh","Microsoft 的 MLOps 五級成熟度模型","Microsoft Azure 把 MLOps 分成五級，從手動訓練到自動監控與重訓。這套模型重點不是打分數，而是看團隊能不能重現、追蹤和自動化模型流程。","industry","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780970578667-kwcy.png","zh","2026-06-09T02:02:30.486328+00:00"]