ML.NET: Sentiment Analysis with Binary Classification
In this article, we will build an ASP.NET Core 10 MVC application that finds out whether a statement typed by the user is Positive or Negative . The training data comes from a SQL Server table, the model is built with ML.NET using binary classification, and the application keeps working correctly when new rows are inserted in the table while it is running. We will go step by step. First we create the database and the table. Then we create the MVC project, add the packages and write the classes one by one. After each piece of code, we will see what the code is doing. At the end we will look closely at how the application handles new rows in the table, including the Refresh model now button that has a 2 minute timer and posts to the server by itself when nobody clicks it. Figure 1: The architecture of the application. The request path is on top and the training path is below it. What is ML.NET? ML.NET is an open source and cross platform machine learning framework from Micros...