ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
Get Started
$ dotnet add package Microsoft.MLReadme
About
ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
For more information, see the ML.NET documentation.
Key Features
- Classification/Categorization - Automatically divide customer feedback into positive and negative categories
- Regression/Predict continuous values - Predict the price of houses based on size and location
- Anomaly Detection - Detect fraudulent banking transactions
- Recommendations - Suggest products that online shoppers may want to buy, based on their previous purchases
- Time series/sequential data - Forecast the weather/product sales
- Image classification - Categorize pathologies in medical images
- Text classification - Categorize documents based on their content.
- Sentence similarity - Measure how similar two sentences are.
How to Use
See Machine Learning Samples for an assortment of samples that show how to get started using ML.NET.
Main Types
Some of the types provided by this library are:
Microsoft.ML.MLContextMicrosoft.ML.ITransformerMicrosoft.ML.IEstimator<TTransformer>
Additional Documentation
Related Packages
- Core data abstraction: Microsoft.ML.DataView
- LightGBM Model Support: Microsoft.ML.LightGbm
- Fast Tree: Microsoft.ML.FastTree
- Image analytics: Microsoft.ML.ImageAnalytics
- Recommender: Microsoft.ML.Recommender
- Time series: Microsoft.ML.TimeSeries
- Automatic model selection / tuning: Microsoft.ML.AutoML
- Exporting Onnx Models: Microsoft.ML.OnnxConverter
- Loading Onnx models: Microsoft.ML.OnnxTransformer
- Text tokenizers: Microsoft.ML.Tokenizers
Feedback & Contributing
Microsoft.ML is released as open source under the MIT license. Bug reports and contributions are welcome at the GitHub repository.