ML.NET Tutorial - Get started in 10 minutes

The ML.NET CLI has generated the trained model and code for you, so you can now use the model in your other .NET applications (for example, your consumeModelApp console app) by following these steps:

1. Copy the generated MLModel.zip file from the SampleClassification.Model folder to the consumeModelApp folder.
2. In the command line, navigate to the consumeModelApp directory.
   Command promptCopy

   cd consumeModelApp

3. Add a reference to the generated class library that contains the trained model and consumption code (SampleClassification.Model) in your consumeModelApp project by running the following command:

   Command promptCopy

   dotnet add reference "../SampleClassification/SampleClassification.Model/SampleClassification.Model.csproj"

4. Open the consumeModelApp Program.cs in any code editor and replace the code with the following:

Program.csCopy

using System;
using SampleClassification.Model;

namespace consumeModelApp
{
    class Program
    {
        static void Main(string[] args)
        {
            // Add input data
            var input = new ModelInput()
            {
              Col0 = "This restaurant was wonderful."
            };

            // Load model and predict output of sample data
            ModelOutput result = ConsumeModel.Predict(input);
            // If Prediction is 1, sentiment is "Positive"; otherwise, sentiment is "Negative"
            string sentiment = result.Prediction == "1" ? "Positive" : "Negative";
            Console.WriteLine($"Text: {input.Col0}\nSentiment: {sentiment}");
        }
    }
}

5. Run your consumeModelApp. You can do this by running the following command in the terminal (make sure you are in the consumeModelApp directory):

   Command promptCopy

   dotnet run

   The output should look something like this: