Deploying an Analytics Model
In the previous chapters, we looked at the differences between distinct types of analytics. We implemented some examples of prognostic and diagnostic analytics in the world of the Industrial Internet of Things (IIoT). We also studied how to deploy our analytics on the most common platforms and how to use open source technologies.
In this chapter, we will finalize our exercise by delivering the algorithms developed in Chapter 14. We want to highlight the most important challenges to building and deploying analytics in production. We will discover the most important cloud platforms and how they provide a computational infrastructure for training and a service-oriented platform for using the analytical model.
In this chapter, we will explore the following topics:
- Deploying digital-twin analytics using the Azure Machine Learning (Azure ML) service
- Understanding analytics on Azure IoT Edge
- Deploying analytics using Amazon SageMaker ...
