The Accord.MachineLearning package includes .NET algorithms for support vector machines, decision trees, and clustering.
Aerosolve
Aerosolve provides a machine learning package with example models and documentation.
About Aerosolve
Aerosolve is a machine learning package built for developers who want to build and inspect models. Its homepage emphasizes feature engineering, with support for geo-based features, controllable quantization, feature interaction, and the ability to specify prior beliefs for a model. It also describes general additive models as a way to balance model capacity with interpretability. The homepage shows an example of neighborhood polygons in San Francisco, generated from listing density using a multi-scale Kd-tree model.
Aerosolve is built on the JVM. Feature training uses Scala, and run-time inference uses a lightweight Java API, so it is aimed at teams integrating machine learning into JVM projects. The homepage does not state pricing, so known pricing is unknown.
Key features
- Geo-based features for machine learning models
- Controllable quantization of model inputs
- Feature interaction support
- Ability to specify prior beliefs for models
- Feature transform language for developer control over features
- Scala for feature training and lightweight Java API for inference
Best for: Developers working in JVM projects who want to engineer features and build interpretable machine learning models.
Good for
- A feature transform language gives the developer full control over features.
- General additive models provide capacity while enabling easy interpretation.
- A lightweight Java API is provided for run-time inference.
Aerosolve at a glance
- Website
- aerosolve.airbnb.tech
- Type
- Website
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Aerosolve FAQ
Which programming languages does Aerosolve use?
Feature training uses Scala, and run-time inference is provided through a lightweight Java API.
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