Chapter 9: Integrating Azure Cognitive Services and Machine Learning
Advanced intelligence efforts are gathering speed and the potential for integrating machine learning models with data processing, for example, to detect fraud, predict device failure, or simply to warn a company before a customer moves on, is promising. The seamless integration of ML models into your data pipelines, and with this the shortest possible time to production, is therefore key.
In this chapter, you are going to examine predefined machine learning models that you can provision and instantly consume as services on Azure. You will learn how to implement them in a Synapse Spark notebook to use them with your data.
In the second part, we will have a look at the Azure Machine Learning service and the available features there. You will examine the graphical interface of Azure ML and learn how to implement your own ML model and expose it to your modern data warehouse environment.
This chapter will not...
