airbnb/aerosolve

Health v2 · maintenance only

Adoption not part of the score

4808 stars · 563 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Aerosolve is a machine learning library from Airbnb built for human-friendly, interpretable modeling on the JVM. It provides a thrift-based feature representation, a feature transform language, debuggable additive models, Scala training code, and a lightweight Java inference API.

Use cases

• build interpretable machine learning models with sparse features
• train ranking models for search results
• model pricing and demand prediction
• debug and visualize feature weights
• engineer geo-based and feature interaction transforms
• serve lightweight Java inference in production
• rank or order images by content

When to choose

• you need interpretable, debuggable models over sparse human-readable features
• you work on the JVM and want Scala training with lightweight Java inference
• your problem involves search ranking, pricing, or demand modeling
• you want fine-grained control over feature transforms and quantization

When to avoid

• you need deep learning on dense inputs like raw pixels or audio
• you want a actively developed library with modern ecosystem support
• you need GPU acceleration or Python-based tooling
• your team is not comfortable with Scala/Java

Facets

library · maturity maintenance

machine-learning nlp image-processing machine-learning data-science developer-tools jvm interpretable-ml feature-engineering ranking sparse-features additive-models scala java

Member repositories

For agents

markdown · JSON · MCP: product_card(name="airbnb/aerosolve")