In machine learning, inferencing
refers to the use of a trained model
to predict labels for new data on which the
model is not been trained. Often the model is
deployed as part of a service that enables
applications to request immediate or
real-time predictions for individual or small numbers
of data observations. In Azure Machine Learning, you can create real-time
inferencing solutions by deploying a
model as a service hosted in a
containerized platform such as Azure Kubernetes
Services or AKS. In this lesson, you
will learn how to deploy a model as a real-time
inferencing service, consumer real-time
inferencing service, and troubleshoot
service deployment.