azuremlsdk

Create a deployment config for deploying an ACI web service

Create a deployment config for deploying an AKS web service

Attach an existing AKS cluster to a workspace

azureml module User can access functions/modules in azureml that are not exposed through the exported R functions.

Define a Bandit policy for early termination of HyperDrive runs

Define Bayesian sampling over a hyperparameter search space

Cancel a run

Specify a discrete set of options to sample from

Mark a run as completed.

Specify Azure Container Registry details

Convert the current dataset into a FileDataset containing CSV files.

Convert the current dataset into a FileDataset containing Parquet files.

Specifies a CRAN package to install in environment

Create an AksCompute cluster

Create an AmlCompute cluster

Create a child run

Create one or many child runs

Create a FileDataset to represent file streams.

Create an unregistered, in-memory Dataset from delimited files.

Create a TabularDataset to represent tabular data in JSON Lines files (http://jsonlines.org/).

Create an unregistered, in-memory Dataset from parquet files.

Create a TabularDataset to represent tabular data in SQL databases.

Create a new Azure Machine Learning workspace

Represents a path to data in a datastore.

Configure conversion to bool.

Configure conversion to datetime.

Configure conversion to 53-bit double.

Configure conversion to 64-bit integer.

Configure conversion to string.

Represent how to deliver the dataset to a compute target.

Define timestamp columns for the dataset.

Delete a cluster

Delete a local web service from the local machine

Delete a model from its associated workspace

Delete secrets from a keyvault

Delete a web service from a given workspace

Delete a workspace

Deploy a web service from registered model(s)

Detach an AksCompute cluster from its associated workspace

Download a file from a run

Download files from a run

Download data from a datastore to the local file system

Download file streams defined by the dataset as local files.

Download a model to the local file system

Drop the specified columns from the dataset.

Create an estimator

Create an Azure Machine Learning experiment

Filter Tabular Dataset with time stamp columns after a specified start time.

Filter Tabular Dataset with time stamp columns before a specified end time.

Filter Tabular Dataset between a specified start and end time.

Filter Tabular Dataset to contain only the specified duration (amount) of recent data.

Generates the control script for the experiment.

Regenerate one of a web service's keys

Get the credentials for an AksCompute cluster

Return the best performing run amongst all completed runs

Get the hyperparameters for all child runs

Get the metrics from all child runs

Get all children for the current run selected by specified filters

Get the child runs sorted in descending order by best primary metric

Get an existing compute cluster

Get the context object for a run

Get Dataset by ID.

Get a registered Dataset from the workspace by its registration name.

Get an existing datastore

Get the default datastore for a workspace

Get the default keyvault for a workspace

Get an existing environment

Get a list of file paths for each file stream defined by the dataset.

Return the named list for input datasets.

Get a registered model

Get the Azure container registry that a packaged model uses

Get the model package creation logs

Get an experiment run

Get the details of a run

Get the details of a run along with the log files' contents

List the files that are stored in association with a run

Get the metrics logged to a run

Return a generator of the runs for an experiment

Get secrets from a keyvault

Get secrets from the keyvault associated with a run's workspace

Get a deployed web service

Retrieve auth keys for a web service

Retrieve the logs for a web service

Retrieve the auth token for a web service

Get an existing workspace

Get the details of a workspace

Specifies a Github package to install in environment

Define grid sampling over a hyperparameter search space

Create a configuration for a HyperDrive run

Create an inference configuration for model deployments

Install azureml sdk package

Manages authentication and acquires an authorization token in interactive login workflows.

Call a web service with the provided input

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

Get the details (e.g IP address, port etc) of all the compute nodes in the compute target

List the secrets in a keyvault

List the supported VM sizes in a region

List all workspaces that the user has access to in a subscription ID

Load all records from the dataset into a dataframe.

Load workspace configuration details from a config file

Create a deployment config for deploying a local web service

Log an accuracy table metric to a run

Log a confusion matrix metric to a run

Log an image metric to a run

Log a vector metric value to a run

Log a metric to a run

Log a predictions metric to a run

Log a residuals metric to a run

Log a row metric to a run

Log a table metric to a run

Specify a normal distribution of the form exp(normal(mu, sigma))

Specify a log uniform distribution

Define a median stopping policy for early termination of HyperDrive runs

Combine the results from the parallel training.

Create a context manager for mounting file streams defined by the dataset as local files.

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

Create a model package that packages all the assets needed to host a model as a web service

Generate table of run details

Define supported metric goals for hyperparameter tuning

Defines options for how column headers are processed when reading data from files to create a dataset.

Pull the Docker image from a ModelPackage to your local Docker environment

Specify a normal distribution of the form round(exp(normal(mu, sigma)) / q) * q

Specify a uniform distribution of the form round(exp(uniform(min_value, max_value) / q) * q

Specify a normal distribution of the form round(normal(mu, sigma) / q) * q

Specify a uniform distribution of the form round(uniform(min_value, max_value) / q) * q

Create an environment

Specify a set of random integers in the range [0, upper)

Define random sampling over a hyperparameter search space

Split file streams in the dataset into two parts randomly and approximately by the percentage specified.

Register an Azure blob container as a datastore

Initialize a new Azure Data Lake Gen2 Datastore.

Register an Azure file share as a datastore

Initialize a new Azure PostgreSQL Datastore.

Initialize a new Azure SQL database Datastore.

Register a Dataset in the workspace

Registers AMLCompute as a parallel backend with the foreach package.

Register an environment in the workspace

Register a model to a given workspace

Register a model for operationalization.

Reload a local web service's entry script and dependencies

Initialize the ResourceConfiguration.

Save a Dockerfile and dependencies from a ModelPackage to your local file system

Manages authentication using a service principle instead of a user identity.

Set the default datastore for a workspace

Add secrets to a keyvault

Skip file streams from the top of the dataset by the specified count.

Splits the job into parallel tasks.

Create an interactive logging run

Submit an experiment and return the active child run

Submit an experiment and return the active created run

Take a sample of file streams from top of the dataset by the specified count.

Take a random sample of file streams in the dataset approximately by the probability specified.

Define a truncation selection policy for early termination of HyperDrive runs

Specify a uniform distribution of options to sample from

Unregister all versions under the registration name of this dataset from the workspace.

Unregister a datastore from its associated workspace

Update a deployed ACI web service

Update a deployed AKS web service

Update scale settings for an AmlCompute cluster

Update a local web service

Upload files to the Azure storage a datastore points to

Upload files to a run

Upload a folder to a run

Upload a local directory to the Azure storage a datastore points to

Initialize run details widget

Wait for a web service to finish deploying

Wait for a model package to finish creating

Wait for a cluster to finish provisioning

Wait for the completion of a run

Write out the workspace configuration details to a config file