Mock sample for your project: Azure Machine Learning Datastore Management Client API

File share operation endpoints and objects.

Virtual Network admin operation endpoints and objects.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

Virtual Machine Image Template

Creates an Azure Data Lake Analytics job client.

These APIs allow end users to operate on Azure Machine Learning Commitment Plans resources and their child Commitment Association resources. They support CRUD operations for commitment plans, get and list operations for commitment associations, moving commitment associations between commitment plans, and retrieving commitment plan usage history.

The Container Service Client.

The Admin Storage Management Client.

Microsoft Customer Engagement Fabric

REST API for Azure Logic Apps.

The HDInsight Management Client.

To manage and control access to your resources, you can define customized policies and assign them at a scope.

The HDInsight Management Client.

Creates an Azure Data Lake Store account management client.

The Azure Management Groups API enables consolidation of multiple subscriptions/resources into an organizational hierarchy and centrally manage access control, policies, alerting and reporting for those resources.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

Resource Provider

The Managed Labs Client.

Personalizer Service is an Azure Cognitive Service that makes it easy to target content and experiences without complex pre-analysis or cleanup of past data. Given a context and featurized content, the Personalizer Service returns which content item to show to users in rewardActionId. As rewards are sent in response to the use of rewardActionId, the reinforcement learning algorithm will improve the model and improve performance of future rank calls.