R: Interface to the 'Azure Machine Learning' 'SDK'

# Interface to the 'Azure Machine Learning' 'SDK'

## Documentation for package ‘azuremlsdk’ version 1.10.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

A B C D E F G H I K L M N P Q R S T U V W

## -- A --

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.

## -- B --

bandit_policy | Define a Bandit policy for early termination of HyperDrive runs
bayesian_parameter_sampling | Define Bayesian sampling over a hyperparameter search space

## -- C --

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

## -- D --

dataset_consumption_config | Represent how to deliver the dataset to a compute target.
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.
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_files_from_run | Download files from a run
download_file_from_run | Download a file 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.

## -- E --

estimator | Create an estimator
experiment | Create an Azure Machine Learning experiment

## -- F --

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.

## -- G --

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_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_child_run_hyperparameters | Get the hyperparameters for all child runs
get_child_run_metrics | Get the metrics from all child runs
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_runs_in_experiment | Return a generator of the runs for an experiment
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_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

## -- H --

hyperdrive_config | Create a configuration for a HyperDrive run

## -- I --

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

## -- K --

keep_columns_from_dataset | Keep the specified columns and drops all others from the dataset.

## -- L --

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
lognormal | Specify a normal distribution of the form 'exp(normal(mu, sigma))'
loguniform | Specify a log uniform distribution
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

## -- M --

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.

## -- N --

normal | Specify a real value that is normally-distributed with mean 'mu' and standard deviation 'sigma'

## -- P --

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

## -- Q --

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 --

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.
r_environment | Create an environment

## -- S --

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

## -- T --

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

## -- U --

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

## -- V --

view_run_details | Initialize run details widget

## -- W --

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