{"id":13689994,"url":"https://github.com/databricks/mlflow","last_synced_at":"2025-05-02T06:31:37.816Z","repository":{"id":49947936,"uuid":"179757651","full_name":"databricks/mlflow","owner":"databricks","description":"Open source platform for the machine learning lifecycle","archived":true,"fork":true,"pushed_at":"2019-04-05T21:20:25.000Z","size":8291,"stargazers_count":94,"open_issues_count":0,"forks_count":42,"subscribers_count":12,"default_branch":"master","last_synced_at":"2025-05-01T02:54:56.951Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://mlflow.org","language":"Python","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":"mlflow/mlflow","license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/databricks.png","metadata":{"files":{"readme":"README.rst","changelog":"CHANGELOG.rst","contributing":"CONTRIBUTING.rst","funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-04-05T21:34:23.000Z","updated_at":"2025-03-17T23:37:21.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/databricks/mlflow","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/databricks%2Fmlflow","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/databricks%2Fmlflow/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/databricks%2Fmlflow/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/databricks%2Fmlflow/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/databricks","download_url":"https://codeload.github.com/databricks/mlflow/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251998533,"owners_count":21677995,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-02T16:00:41.122Z","updated_at":"2025-05-02T06:31:36.679Z","avatar_url":"https://github.com/databricks.png","language":"Python","readme":"===================\nMLflow Beta Release\n===================\n\n**Note:** The current version of MLflow is a beta release. This means that APIs and data formats\nare subject to change!\n\n**Note 2:** We do not currently support running MLflow on Windows. Despite this, we would appreciate any contributions\nto make MLflow work better on Windows.\n\nInstalling\n----------\nInstall MLflow from PyPi via ``pip install mlflow``\n\nMLflow requires ``conda`` to be on the ``PATH`` for the projects feature.\n\nNightly snapshots of MLflow master are also available `here \u003chttps://mlflow-snapshots.s3-us-west-2.amazonaws.com/\u003e`_.\n\nDocumentation\n-------------\nOfficial documentation for MLflow can be found at https://mlflow.org/docs/latest/index.html.\n\nCommunity\n---------\nTo discuss MLflow or get help, please subscribe to our mailing list (mlflow-users@googlegroups.com) or\njoin us on Slack at https://tinyurl.com/mlflow-slack.\n\nTo report bugs, please use GitHub issues.\n\nRunning a Sample App With the Tracking API\n------------------------------------------\nThe programs in ``examples`` use the MLflow Tracking API. For instance, run::\n\n    python examples/quickstart/mlflow_tracking.py\n\nThis program will use `MLflow Tracking API \u003chttps://mlflow.org/docs/latest/tracking.html\u003e`_,\nwhich logs tracking data in ``./mlruns``. This can then be viewed with the Tracking UI.\n\n\nLaunching the Tracking UI\n-------------------------\nThe MLflow Tracking UI will show runs logged in ``./mlruns`` at `\u003chttp://localhost:5000\u003e`_.\nStart it with::\n\n    mlflow ui\n\n**Note:** Running ``mlflow ui`` from within a clone of MLflow is not recommended - doing so will\nrun the dev UI from source. We recommend running the UI from a different working directory, using the\n``--file-store`` option to specify which log directory to run against. Alternatively, see instructions\nfor running the dev UI in the `contributor guide \u003cCONTRIBUTING.rst\u003e`_.\n\n\nRunning a Project from a URI\n----------------------------\nThe ``mlflow run`` command lets you run a project packaged with a MLproject file from a local path\nor a Git URI::\n\n    mlflow run examples/sklearn_elasticnet_wine -P alpha=0.4\n\n    mlflow run https://github.com/mlflow/mlflow-example.git -P alpha=0.4\n\nSee ``examples/sklearn_elasticnet_wine`` for a sample project with an MLproject file.\n\n\nSaving and Serving Models\n-------------------------\nTo illustrate managing models, the ``mlflow.sklearn`` package can log scikit-learn models as\nMLflow artifacts and then load them again for serving. There is an example training application in\n``examples/sklearn_logisitic_regression/train.py`` that you can run as follows::\n\n    $ python examples/sklearn_logisitic_regression/train.py\n    Score: 0.666\n    Model saved in run \u003crun-id\u003e\n\n    $ mlflow sklearn serve -r \u003crun-id\u003e -m model\n\n    $ curl -d '[{\"x\": 1}, {\"x\": -1}]' -H 'Content-Type: application/json' -X POST localhost:5000/invocations\n\n\n\n\n\nContributing\n------------\nWe happily welcome contributions to MLflow. Please see our `contribution guide \u003cCONTRIBUTING.rst\u003e`_\nfor details.\n","funding_links":[],"categories":["Deployment","Software"],"sub_categories":["Ranking/Recommender","Managing building and deploying models"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatabricks%2Fmlflow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdatabricks%2Fmlflow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatabricks%2Fmlflow/lists"}