Hands-On Machine Learning with Azure

ACI

As a data scientist, after we have trained our machine learning model, we may want to deploy the model as a web service for real-time or batch scoring. When we train our machine learning model, we use a certain framework and libraries. In most cases, the same environment should be available in our deployment environment. Containers are a fast and simple way to create such an environment, in which we can host our model and dependencies. Containers can be created easily with ACI. As data scientists, we can use AML to deploy our machine learning model as a web service to an ACI. This way, we can development test our model and then deploy it in production. For more details on ACI, refer to the following website: https://docs.microsoft.com/en-us/azure/container-instances/container-instances-overview ...