diff --git a/README.rst b/README.rst index d96d7d064a648..f4b9750cbc9d2 100644 --- a/README.rst +++ b/README.rst @@ -55,20 +55,20 @@ Running a Project from a URI The ``mlflow run`` command lets you run a project packaged with a MLproject file from a local path or a Git URI:: - mlflow run example/tutorial -P alpha=0.4 + mlflow run examples/sklearn_elasticnet_wine -P alpha=0.4 mlflow run git@github.com:mlflow/mlflow-example.git -P alpha=0.4 -See ``example/tutorial`` for a sample project with an MLproject file. +See ``examples/sklearn_elasticnet_wine`` for a sample project with an MLproject file. Saving and Serving Models ------------------------- 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 -``example/quickstart/test_sklearn.py`` that you can run as follows:: +``examples/sklearn_logisitic_regression/train.py`` that you can run as follows:: - $ python example/quickstart/test_sklearn.py + $ python examples/sklearn_logisitic_regression/train.py Score: 0.666 Model saved in run