Demonstrates how to use ML.NET and Oxyplot to implement some Machine Learning use cases in an MVVM UWP app. Currently works against ML.NET v1.3.1 and is tested against v1.4.0-preview.

If you want to see these same ML.NET scenarios in Jupyter Notebooks and XPlot, then visit https://github.com/XamlBrewer/ML.NET-Jupyter-Notebooks.

The UWP app demonstrates the following Machine Learning scenarios:

• Clustering
• Multiclass Classification
• Binary Classification
• Regression
• Feature Contribution Calculation
• Permutation Feature Importance Calculation
• Recommendation
• Recommendation using Field-Aware Factorization Machine
• Automated model generation with AutoML
• Feature Distribution Analysis with Boxplot Diagrams
• Feature Correlation Analysis with Heatmap Diagrams