Infer
A Clojure library for machine learning and statistical inference designed for production deployment and composable algorithms.
What is Infer?
Infer is a machine learning and statistical inference library built in Clojure, specifically designed for deployment in real production systems. It enables researchers to deploy their analysis code directly without rewriting it for production environments, bridging the gap between research and deployment. The library provides composable abstractions for algorithms, measures, models, and learning methods, unlike traditional siloed libraries.
Clojure developers and data scientists who need to deploy machine learning models from research directly into production, especially in JVM-based environments or distributed systems like Hadoop. It is also suitable for researchers who want composable machine learning components for experimentation.
Developers choose Infer because it allows research code to be deployed to production without rewriting in languages like C++ or Java, saving time and reducing errors. Its composable abstractions and scalability from local to distributed clusters (e.g., Hadoop) offer flexibility not found in traditional siloed libraries like R or Weka.
Overview
inference and machine learning in clojure
Use Cases
Best For
- Deploying machine learning research code directly to production without rewriting in C++ or Java.
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