同步操作将从 Gitee 极速下载/MLflow 强制同步,此操作会覆盖自 Fork 仓库以来所做的任何修改,且无法恢复!!!
确定后同步将在后台操作,完成时将刷新页面,请耐心等待。
Note: The current version of MLflow is a beta release. This means that APIs and data formats are subject to change!
Note 2: We do not currently support running MLflow on Windows. Despite this, we would appreciate any contributions to make MLflow work better on Windows.
Install MLflow from PyPi via pip install mlflow
MLflow requires conda to be on the PATH for the projects feature.
Nightly snapshots of MLflow master are also available Documentation
Official documentation for MLflow can be found at Community
To discuss MLflow or get help, please subscribe to our mailing list (mlflow-users@googlegroups.com) or join us on Slack at Running a Sample App With the Tracking API
The programs in examples use the MLflow Tracking API. For instance, run:
python examples/quickstart/mlflow_tracking.py
This program will use Launching the Tracking UI
The MLflow Tracking UI will show runs logged in ./mlruns at contributor guide.
The mlflow run command lets you run a project packaged with a MLproject file from a local path
or a Git URI:
mlflow run examples/sklearn_elasticnet_wine -P alpha=0.4 mlflow run https://github.com/mlflow/mlflow-example.git -P alpha=0.4
See examples/sklearn_elasticnet_wine for a sample project with an MLproject file.
To illustrate managing models, the mlflow.sklearn package can log scikit-learn models as
MLflow artifacts and then load them again for serving. There is an example training application in
examples/sklearn_logisitic_regression/train.py that you can run as follows:
$ python examples/sklearn_logisitic_regression/train.py
Score: 0.666
Model saved in run <run-id>
$ mlflow sklearn serve -r <run-id> -m model
$ curl -d '[{"x": 1}, {"x": -1}]' -H 'Content-Type: application/json' -X POST localhost:5000/invocations
We happily welcome contributions to MLflow. Please see our contribution guide for details.
此处可能存在不合适展示的内容,页面不予展示。您可通过相关编辑功能自查并修改。
如您确认内容无涉及 不当用语 / 纯广告导流 / 暴力 / 低俗色情 / 侵权 / 盗版 / 虚假 / 无价值内容或违法国家有关法律法规的内容,可点击提交进行申诉,我们将尽快为您处理。