haifengl/smile

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

6413 stars · 1148 forks observed · 2026-08-28

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

SMILE is a comprehensive, high-performance machine learning framework for the JVM with idiomatic APIs for Java, Scala, and Kotlin. It covers classification, regression, clustering, manifold learning, NLP, deep learning, and LLM inference, plus visualization and a data science IDE (SMILE Studio).

Use cases

• train classifiers like random forest or svm on the jvm
• run llama-3 llm inference in java
• cluster data with k-means or dbscan in scala
• dimensionality reduction with t-sne or umap
• build a data science pipeline in kotlin
• tokenize and tag part-of-speech in text
• visualize machine learning results

When to choose

• you need a fast, batteries-included ML library on the JVM
• you want Scala or Kotlin idiomatic ML APIs
• you need classical ML, NLP, and deep learning in one dependency

When to avoid

• you primarily work in Python with scikit-learn or PyTorch ecosystems
• you need cutting-edge research models not implemented in SMILE
• your project is not on the JVM

Facets

library · maturity active

machine-learning deep-learning llm-inference nlp data-visualization math data-science machine-learning deep-learning large-language-models data-science computer-vision jvm cross-platform scala kotlin classification clustering regression manifold-learning statistics dataframe smile-studio natural-language-processing

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markdown · JSON · MCP: product_card(name="haifengl/smile")