Real-Time Machine Learning with Azure ML Endpoints
Are you using the most appropriate machine learning approach for your use case?
Some machine learning tasks can be completed in real-time, while others require batch processing. This talk will compare and contrast the pros and cons of both approaches, so that you can learn the differences between batch inference and real-time inference. You will also learn how to do real-time ML using both the classic experience (Azure Container Instances/Azure Kubernetes Services) and the new Azure ML Endpoints, going from deploying a simple ML model to both ACI and AML Endpoints, to discussing the differences and similarities between the two, and iterating the changes you will need to make in order to get a production-ready service.
By the end of this talk, you'll know how to deploy a real-time machine learning model using Azure ML Endpoints.