In this chapter, we have implemented the integration of Azure Functions with the Microsoft Cognitive Services text sentiment analytics API. This integration allowed us to leverage the depth and breadth of Microsoft knowledge based on historical data, Machine Learning, and artificial intelligence to analyze the sentiment of input text.
We also expanded on the approach of using shared code across multiple Azure Functions to encapsulate functionality that is needed across the board, and we integrated the new results from a Twitter feed and document analysis with our Web UI dashboard.
During the previous four chapters, we walked through how to design and build a full text sentiment analytics application for analyzing text documents and tweets based on Azure serverless compute (Azure Functions), with a SQL Azure database as a data store and .NET Core Web application as a GUI.
As reflected in the architecture diagram in the beginning of this chapter, the application is comprised of multiple...