.NET Machine learning how-to guides

In the How to section of the ML.NET Guide, you can find quick answers to common questions. In some cases, articles might be listed in multiple sections to make them easy to find.

Load data

• Load data from files and SQL databases.

Prepare the data

• Preprocess training data with normalizers to use in data processing.

Train the model

• Train a machine learning model using cross-validation.

• Train a regression model to predict a value using ML.NET.

Model explainability

• Determine the feature importance of models with Permutation Feature Importance.

Run

• Inspect intermediate data values during ML.NET pipeline processing.

• Load a trained machine learning model.

• Make predictions with a trained model.

Probabilistic (Infer.NET)

• Create a game match up list app with Infer.NET and probabilistic programming.