{"id":533141,"date":"2026-03-27T10:14:45","date_gmt":"2026-03-27T03:14:45","guid":{"rendered":"https:\/\/hoanghamobile.com\/tin-tuc\/?p=533141"},"modified":"2026-04-17T21:10:42","modified_gmt":"2026-04-17T14:10:42","slug":"mlflow","status":"publish","type":"post","link":"https:\/\/hoanghamobile.com\/tin-tuc\/mlflow\/","title":{"rendered":"MLflow: Gi\u1ea3i ph\u00e1p To\u00e0n di\u1ec7n Qu\u1ea3n l\u00fd V\u00f2ng \u0111\u1eddi H\u1ecdc m\u00e1y (MLOps)"},"content":{"rendered":"

MLflow<\/b> l\u00e0 m\u1ed9t n\u1ec1n t\u1ea3ng m\u00e3 ngu\u1ed3n m\u1edf h\u1ed7 tr\u1ee3 qu\u1ea3n l\u00fd to\u00e0n b\u1ed9 v\u00f2ng \u0111\u1eddi h\u1ecdc m\u00e1y (ML lifecycle), t\u1eeb l\u00ean \u00fd t\u01b0\u1edfng, th\u1eed nghi\u1ec7m, tri\u1ec3n khai t\u1edbi gi\u00e1m s\u00e1t m\u00f4 h\u00ecnh. C\u00f4ng c\u1ee5 n\u00e0y gi\u00fap c\u00e1c nh\u00f3m Data Scientist v\u00e0 ML Engineer l\u01b0u tr\u1eef, t\u00e1i t\u1ea1o v\u00e0 t\u1ed1i \u01b0u h\u00f3a quy tr\u00ecnh ph\u00e1t tri\u1ec3n m\u00f4 h\u00ecnh m\u1ed9t c\u00e1ch hi\u1ec7u qu\u1ea3 v\u00e0 minh b\u1ea1ch.<\/span><\/p>\n

MLflow l\u00e0 g\u00ec? T\u1ed5ng quan v\u1ec1 n\u1ec1n t\u1ea3ng MLOps m\u00e3 ngu\u1ed3n m\u1edf<\/b><\/h2>\n

Machine Learning Lifecycle Platform l\u00e0 m\u1ed9t n\u1ec1n t\u1ea3ng m\u00e3 ngu\u1ed3n m\u1edf \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n b\u1edfi Databricks t\u1eeb n\u0103m 2018, nh\u1eb1m cung c\u1ea5p gi\u1ea3i ph\u00e1p to\u00e0n di\u1ec7n cho <\/span>qu\u1ea3n l\u00fd v\u00f2ng \u0111\u1eddi h\u1ecdc m\u00e1y<\/b>. T\u1eeb kh\u00e2u th\u1eed nghi\u1ec7m, ph\u00e1t tri\u1ec3n, tri\u1ec3n khai \u0111\u1ebfn gi\u00e1m s\u00e1t m\u00f4 h\u00ecnh, ML experiment tracking tool mang t\u1edbi m\u1ed9t b\u1ed9 c\u00f4ng c\u1ee5 chu\u1ea9n h\u00f3a quy tr\u00ecnh MLOps cho c\u1ea3 c\u00e1 nh\u00e2n v\u00e0 t\u1ed5 ch\u1ee9c.<\/span><\/p>\n

\"MLflow-1\"<\/p>\n

M\u1ee5c ti\u00eau c\u1ed1t l\u00f5i c\u1ee7a Machine Learning Lifecycle Platform l\u00e0 gi\u00fap c\u00e1c nh\u00f3m ML chu\u1ea9n h\u00f3a pipeline ph\u00e1t tri\u1ec3n, gi\u1ea3m thi\u1ec3u r\u1ee7i ro th\u1ea5t l\u1ea1c th\u00f4ng s\u1ed1, m\u1ea5t ki\u1ec3m so\u00e1t version, \u0111\u1ed3ng th\u1eddi t\u0103ng kh\u1ea3 n\u0103ng t\u00e1i t\u1ea1o v\u00e0 h\u1ee3p t\u00e1c. N\u1ec1n t\u1ea3ng bao g\u1ed3m: <\/span>Tracking<\/b> (theo d\u00f5i th\u00ed nghi\u1ec7m), <\/span>Projects<\/b> (\u0111\u00f3ng g\u00f3i m\u00e3 & m\u00f4i tr\u01b0\u1eddng), <\/span>Models<\/b> (qu\u1ea3n l\u00fd, l\u01b0u tr\u1eef, ph\u1ee5c v\u1ee5 m\u00f4 h\u00ecnh), v\u00e0 <\/span>Model Registry<\/b> (qu\u1ea3n l\u00fd version model, approval, lifecycle).<\/span><\/p>\n

L\u1ee3i \u00edch c\u1ee7a Machine Learning Lifecycle Platform trong machine learning<\/b> l\u00e0 g\u00ec? \u0110\u00f3 l\u00e0 t\u0103ng t\u1ed1c \u0111\u1ed9 ph\u00e1t tri\u1ec3n m\u00f4 h\u00ecnh nh\u1edd l\u01b0u tr\u1eef \u0111\u1ea7y \u0111\u1ee7 th\u00f4ng s\u1ed1 v\u00e0 k\u1ebft qu\u1ea3, \u0111\u1ea3m b\u1ea3o kh\u1ea3 n\u0103ng t\u00e1i t\u1ea1o th\u00ed nghi\u1ec7m, ki\u1ec3m so\u00e1t version v\u00e0 ph\u1ee5c v\u1ee5 m\u00f4 h\u00ecnh ch\u1ee7 \u0111\u1ed9ng. N\u1ec1n t\u1ea3ng c\u00f2n gi\u00fap ti\u1ebft ki\u1ec7m th\u1eddi gian khi chuy\u1ec3n giao d\u1ef1 \u00e1n, h\u1ed7 tr\u1ee3 c\u1ed9ng t\u00e1c nh\u00f3m, \u0111\u1ed3ng th\u1eddi d\u1ec5 d\u00e0ng t\u00edch h\u1ee3p v\u1edbi c\u00e1c h\u1ec7 th\u1ed1ng hi\u1ec7n \u0111\u1ea1i nh\u01b0 cloud, Docker, Kubernetes, Databricks ho\u1eb7c c\u00e1c framework ML ph\u1ed5 bi\u1ebfn.<\/span><\/p>\n

C\u00e1c th\u00e0nh ph\u1ea7n v\u00e0 ch\u1ee9c n\u0103ng ch\u00ednh c\u1ee7a MLflow<\/b><\/h2>\n

N\u1ec1n t\u1ea3ng \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf v\u1edbi b\u1ed1n th\u00e0nh ph\u1ea7n ch\u00ednh, m\u1ed7i ph\u1ea7n \u0111\u1ea3m nh\u1eadn m\u1ed9t vai tr\u00f2 ri\u00eang bi\u1ec7t trong qu\u1ea3n l\u00fd v\u00e0 t\u1ed1i \u01b0u v\u00f2ng \u0111\u1eddi h\u1ecdc m\u00e1y. Vi\u1ec7c hi\u1ec3u r\u00f5 t\u1eebng th\u00e0nh ph\u1ea7n l\u00e0 ch\u00eca kh\u00f3a \u0111\u1ec3 t\u1eadn d\u1ee5ng t\u1ed1i \u0111a s\u1ee9c m\u1ea1nh c\u1ee7a ph\u01b0\u01a1ng th\u1ee9c trong d\u1ef1 \u00e1n th\u1ef1c t\u1ebf.<\/span><\/p>\n

Tracking: Theo d\u00f5i v\u00e0 qu\u1ea3n l\u00fd th\u00ed nghi\u1ec7m h\u1ecdc m\u00e1y<\/b><\/h3>\n

Tracking<\/b> l\u00e0 \u201ctr\u00e1i tim\u201d c\u1ee7a n\u1ec1n t\u1ea3ng, gi\u00fap b\u1ea1n ghi l\u1ea1i, l\u01b0u tr\u1eef v\u00e0 so s\u00e1nh m\u1ecdi th\u00f4ng s\u1ed1 (parameters), ch\u1ec9 s\u1ed1 \u0111\u00e1nh gi\u00e1 (metrics), v\u00e0 artifacts (file, m\u00f4 h\u00ecnh, log) c\u1ee7a t\u1eebng l\u1ea7n ch\u1ea1y m\u00f4 h\u00ecnh (run). \u0110i\u1ec1u n\u00e0y gi\u1ea3i quy\u1ebft tri\u1ec7t \u0111\u1ec3 v\u1ea5n \u0111\u1ec1: l\u00e0m sao \u0111\u1ec3 kh\u00f4ng \u201cl\u1ea1c m\u1ea5t\u201d k\u1ebft qu\u1ea3 ho\u1eb7c kh\u00f4ng bi\u1ebft run n\u00e0o cho ra model t\u1ed1t nh\u1ea5t!<\/span>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0<\/span><\/p>\n