submit_experiment: Submit an experiment and return the active created run
In azuremlsdk: Interface to the 'Azure Machine Learning' 'SDK'

Description Usage Arguments Value See Also Examples

submit_experiment() is an asynchronous call to Azure Machine Learning service to execute a trial on local or remote compute. Depending on the configuration, submit_experiment() will automatically prepare your execution environments, execute your code, and capture your source code and results in the experiment's run history.

To submit an experiment you first need to create a configuration object describing how the experiment is to be run. The configuration depends on the type of trial required. For a script run, provide an Estimator object to the config parameter. For a HyperDrive run for hyperparameter tuning, provide a HyperDriveConfig to config.

1	submit_experiment(experiment, config, tags = NULL)

`experiment`	The `Experiment` object.
`config`	The `Estimator` or `HyperDriveConfig` object.
`tags`	A named list of tags for the submitted run, e.g. `list("tag" = "value")`.

The ScriptRun or HyperDriveRun object.

estimator(), hyperdrive_config()

# This example submits an Estimator experiment
## Not run: 
ws <- load_workspace_from_config()
compute_target <- get_compute(ws, cluster_name = 'mycluster')
exp <- experiment(ws, name = 'myexperiment')
est <- estimator(source_directory = '.',
                 entry_script = 'train.R',
                 compute_target = compute_target)
run <- submit_experiment(exp, est)

## End(Not run)