Summary
In this chapter, you have learned about several predefined cognitive services on Azure and how to use them in your modern data warehouse. You have created a Spark notebook and analyzed the sentiment of a given text with the Text Analytics cognitive service.
In the second part of the chapter, you examined the Azure Machine Learning service. This can be seen as one of the central services on Azure when it comes to the implementation of Machine Learning and AI.
You have learned about the different options that a data scientist finds in Azure ML and have implemented your own machine learning model using the graphical designer of Azure ML.
Finally, you connected Azure ML to your Synapse workspace and integrated the ML model with a Synapse pipeline.
Additionally, we discussed other options for integrating Azure ML with your modern data warehouse.
In the upcoming chapter, Implementing the Presentation Layer with Synapse Analytics, we will examine how to import, model...
