aci_webservice_deployment_config
                        Create a deployment config for deploying an ACI
                        web service
aks_webservice_deployment_config
                        Create a deployment config for deploying an AKS
                        web service
attach_aks_compute      Attach an existing AKS cluster to a workspace
azureml                 azureml module User can access
                        functions/modules in azureml that are not
                        exposed through the exported R functions.
bandit_policy           Define a Bandit policy for early termination of
                        HyperDrive runs
bayesian_parameter_sampling
                        Define Bayesian sampling over a hyperparameter
                        search space
cancel_run              Cancel a run
choice                  Specify a discrete set of options to sample
                        from
complete_run            Mark a run as completed.
container_registry      Specify Azure Container Registry details
convert_to_dataset_with_csv_files
                        Convert the current dataset into a FileDataset
                        containing CSV files.
convert_to_dataset_with_parquet_files
                        Convert the current dataset into a FileDataset
                        containing Parquet files.
cran_package            Specifies a CRAN package to install in
                        environment
create_aks_compute      Create an AksCompute cluster
create_aml_compute      Create an AmlCompute cluster
create_child_run        Create a child run
create_child_runs       Create one or many child runs
create_file_dataset_from_files
                        Create a FileDataset to represent file streams.
create_tabular_dataset_from_delimited_files
                        Create an unregistered, in-memory Dataset from
                        delimited files.
create_tabular_dataset_from_json_lines_files
                        Create a TabularDataset to represent tabular
                        data in JSON Lines files
                        (http://jsonlines.org/).
create_tabular_dataset_from_parquet_files
                        Create an unregistered, in-memory Dataset from
                        parquet files.
create_tabular_dataset_from_sql_query
                        Create a TabularDataset to represent tabular
                        data in SQL databases.
create_workspace        Create a new Azure Machine Learning workspace
data_path               Represents a path to data in a datastore.
data_type_bool          Configure conversion to bool.
data_type_datetime      Configure conversion to datetime.
data_type_double        Configure conversion to 53-bit double.
data_type_long          Configure conversion to 64-bit integer.
data_type_string        Configure conversion to string.
dataset_consumption_config
                        Represent how to deliver the dataset to a
                        compute target.
define_timestamp_columns_for_dataset
                        Define timestamp columns for the dataset.
delete_compute          Delete a cluster
delete_local_webservice
                        Delete a local web service from the local
                        machine
delete_model            Delete a model from its associated workspace
delete_secrets          Delete secrets from a keyvault
delete_webservice       Delete a web service from a given workspace
delete_workspace        Delete a workspace
deploy_model            Deploy a web service from registered model(s)
detach_aks_compute      Detach an AksCompute cluster from its
                        associated workspace
download_file_from_run
                        Download a file from a run
download_files_from_run
                        Download files from a run
download_from_datastore
                        Download data from a datastore to the local
                        file system
download_from_file_dataset
                        Download file streams defined by the dataset as
                        local files.
download_model          Download a model to the local file system
drop_columns_from_dataset
                        Drop the specified columns from the dataset.
estimator               Create an estimator
experiment              Create an Azure Machine Learning experiment
filter_dataset_after_time
                        Filter Tabular Dataset with time stamp columns
                        after a specified start time.
filter_dataset_before_time
                        Filter Tabular Dataset with time stamp columns
                        before a specified end time.
filter_dataset_between_time
                        Filter Tabular Dataset between a specified
                        start and end time.
filter_dataset_from_recent_time
                        Filter Tabular Dataset to contain only the
                        specified duration (amount) of recent data.
generate_entry_script   Generates the control script for the
                        experiment.
generate_new_webservice_key
                        Regenerate one of a web service's keys
get_aks_compute_credentials
                        Get the credentials for an AksCompute cluster
get_best_run_by_primary_metric
                        Return the best performing run amongst all
                        completed runs
get_child_run_hyperparameters
                        Get the hyperparameters for all child runs
get_child_run_metrics   Get the metrics from all child runs
get_child_runs          Get all children for the current run selected
                        by specified filters
get_child_runs_sorted_by_primary_metric
                        Get the child runs sorted in descending order
                        by best primary metric
get_compute             Get an existing compute cluster
get_current_run         Get the context object for a run
get_dataset_by_id       Get Dataset by ID.
get_dataset_by_name     Get a registered Dataset from the workspace by
                        its registration name.
get_datastore           Get an existing datastore
get_default_datastore   Get the default datastore for a workspace
get_default_keyvault    Get the default keyvault for a workspace
get_environment         Get an existing environment
get_file_dataset_paths
                        Get a list of file paths for each file stream
                        defined by the dataset.
get_input_dataset_from_run
                        Return the named list for input datasets.
get_model               Get a registered model
get_model_package_container_registry
                        Get the Azure container registry that a
                        packaged model uses
get_model_package_creation_logs
                        Get the model package creation logs
get_run                 Get an experiment run
get_run_details         Get the details of a run
get_run_details_with_logs
                        Get the details of a run along with the log
                        files' contents
get_run_file_names      List the files that are stored in association
                        with a run
get_run_metrics         Get the metrics logged to a run
get_runs_in_experiment
                        Return a generator of the runs for an
                        experiment
get_secrets             Get secrets from a keyvault
get_secrets_from_run    Get secrets from the keyvault associated with a
                        run's workspace
get_webservice          Get a deployed web service
get_webservice_keys     Retrieve auth keys for a web service
get_webservice_logs     Retrieve the logs for a web service
get_webservice_token    Retrieve the auth token for a web service
get_workspace           Get an existing workspace
get_workspace_details   Get the details of a workspace
github_package          Specifies a Github package to install in
                        environment
grid_parameter_sampling
                        Define grid sampling over a hyperparameter
                        search space
hyperdrive_config       Create a configuration for a HyperDrive run
inference_config        Create an inference configuration for model
                        deployments
install_azureml         Install azureml sdk package
interactive_login_authentication
                        Manages authentication and acquires an
                        authorization token in interactive login
                        workflows.
invoke_webservice       Call a web service with the provided input
keep_columns_from_dataset
                        Keep the specified columns and drops all others
                        from the dataset.
list_nodes_in_aml_compute
                        Get the details (e.g IP address, port etc) of
                        all the compute nodes in the compute target
list_secrets            List the secrets in a keyvault
list_supported_vm_sizes
                        List the supported VM sizes in a region
list_workspaces         List all workspaces that the user has access to
                        in a subscription ID
load_dataset_into_data_frame
                        Load all records from the dataset into a
                        dataframe.
load_workspace_from_config
                        Load workspace configuration details from a
                        config file
local_webservice_deployment_config
                        Create a deployment config for deploying a
                        local web service
log_accuracy_table_to_run
                        Log an accuracy table metric to a run
log_confusion_matrix_to_run
                        Log a confusion matrix metric to a run
log_image_to_run        Log an image metric to a run
log_list_to_run         Log a vector metric value to a run
log_metric_to_run       Log a metric to a run
log_predictions_to_run
                        Log a predictions metric to a run
log_residuals_to_run    Log a residuals metric to a run
log_row_to_run          Log a row metric to a run
log_table_to_run        Log a table metric to a run
lognormal               Specify a normal distribution of the form
                        'exp(normal(mu, sigma))'
loguniform              Specify a log uniform distribution
median_stopping_policy
                        Define a median stopping policy for early
                        termination of HyperDrive runs
merge_results           Combine the results from the parallel training.
mount_file_dataset      Create a context manager for mounting file
                        streams defined by the dataset as local files.
normal                  Specify a real value that is
                        normally-distributed with mean 'mu' and
                        standard deviation 'sigma'
package_model           Create a model package that packages all the
                        assets needed to host a model as a web service
plot_run_details        Generate table of run details
primary_metric_goal     Define supported metric goals for
                        hyperparameter tuning
promote_headers_behavior
                        Defines options for how column headers are
                        processed when reading data from files to
                        create a dataset.
pull_model_package_image
                        Pull the Docker image from a 'ModelPackage' to
                        your local Docker environment
qlognormal              Specify a normal distribution of the form
                        'round(exp(normal(mu, sigma)) / q) * q'
qloguniform             Specify a uniform distribution of the form
                        round(exp(uniform(min_value, max_value) / q) *
                        q
qnormal                 Specify a normal distribution of the form
                        round(normal(mu, sigma) / q) * q
quniform                Specify a uniform distribution of the form
                        'round(uniform(min_value, max_value) / q) * q'
r_environment           Create an environment
randint                 Specify a set of random integers in the range
                        [0, upper)
random_parameter_sampling
                        Define random sampling over a hyperparameter
                        search space
random_split_dataset    Split file streams in the dataset into two
                        parts randomly and approximately by the
                        percentage specified.
register_azure_blob_container_datastore
                        Register an Azure blob container as a datastore
register_azure_data_lake_gen2_datastore
                        Initialize a new Azure Data Lake Gen2
                        Datastore.
register_azure_file_share_datastore
                        Register an Azure file share as a datastore
register_azure_postgre_sql_datastore
                        Initialize a new Azure PostgreSQL Datastore.
register_azure_sql_database_datastore
                        Initialize a new Azure SQL database Datastore.
register_dataset        Register a Dataset in the workspace
register_do_azureml_parallel
                        Registers AMLCompute as a parallel backend with
                        the foreach package.
register_environment    Register an environment in the workspace
register_model          Register a model to a given workspace
register_model_from_run
                        Register a model for operationalization.
reload_local_webservice_assets
                        Reload a local web service's entry script and
                        dependencies
resource_configuration
                        Initialize the ResourceConfiguration.
save_model_package_files
                        Save a Dockerfile and dependencies from a
                        'ModelPackage' to your local file system
service_principal_authentication
                        Manages authentication using a service
                        principle instead of a user identity.
set_default_datastore   Set the default datastore for a workspace
set_secrets             Add secrets to a keyvault
skip_from_dataset       Skip file streams from the top of the dataset
                        by the specified count.
split_tasks             Splits the job into parallel tasks.
start_logging_run       Create an interactive logging run
submit_child_run        Submit an experiment and return the active
                        child run
submit_experiment       Submit an experiment and return the active
                        created run
take_from_dataset       Take a sample of file streams from top of the
                        dataset by the specified count.
take_sample_from_dataset
                        Take a random sample of file streams in the
                        dataset approximately by the probability
                        specified.
truncation_selection_policy
                        Define a truncation selection policy for early
                        termination of HyperDrive runs
uniform                 Specify a uniform distribution of options to
                        sample from
unregister_all_dataset_versions
                        Unregister all versions under the registration
                        name of this dataset from the workspace.
unregister_datastore    Unregister a datastore from its associated
                        workspace
update_aci_webservice   Update a deployed ACI web service
update_aks_webservice   Update a deployed AKS web service
update_aml_compute      Update scale settings for an AmlCompute cluster
update_local_webservice
                        Update a local web service
upload_files_to_datastore
                        Upload files to the Azure storage a datastore
                        points to
upload_files_to_run     Upload files to a run
upload_folder_to_run    Upload a folder to a run
upload_to_datastore     Upload a local directory to the Azure storage a
                        datastore points to
view_run_details        Initialize run details widget
wait_for_deployment     Wait for a web service to finish deploying
wait_for_model_package_creation
                        Wait for a model package to finish creating
wait_for_provisioning_completion
                        Wait for a cluster to finish provisioning
wait_for_run_completion
                        Wait for the completion of a run
write_workspace_config
                        Write out the workspace configuration details
                        to a config file
