ML.NET tutorials

The following tutorials enable you to understand how to use ML.NET to build custom machine learning solutions and integrate them into your .NET applications:

  • Sentiment analysis: demonstrates how to apply a binary classification task using ML.NET.
  • GitHub issue classification: demonstrates how to apply a multiclass classification task using ML.NET.
  • Price predictor: demonstrates how to apply a regression task using ML.NET.
  • Iris clustering: demonstrates how to apply a clustering task using ML.NET.
  • Recommendation: generate movie recommendations based on previous user ratings
  • Image classification: demonstrates how to retrain an existing TensorFlow model to create a custom image classifier using ML.NET.
  • Anomaly detection: demonstrates how to build an anomaly detection application for product sales data analysis.

Next Steps

For more examples that use ML.NET, check out the dotnet/machinelearning-samples GitHub repository.