Which Azure tool can assist in deploying machine learning models as REST APIs?

Azure Machine Learning is designed specifically to facilitate the end-to-end machine learning lifecycle, which includes model training, deployment, and management. One of its key features is the ability to deploy trained machine learning models as REST APIs. This allows developers to easily integrate and utilize the models in various applications and services. By leveraging Azure Machine Learning, users can create a web service around their models, making them accessible via a simple HTTP endpoint. This functionality promotes scalability and ease of access for applications that need to utilize the machine learning model for predictions.

The other options, while part of the Azure ecosystem, do not directly support the deployment of machine learning models as REST APIs in the same way. Azure SQL Database and Azure Cosmos DB are primarily databases designed for data storage, whereas Azure DevOps focuses on software development and project management activities, including continuous integration and delivery. These tools serve different purposes and do not provide the specific functionality needed for deploying machine learning models as APIs.