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A curated list of libraries, tutorials, and resources for implementing machine learning in the Ruby programming language.
A curated list of awesome libraries, data sources, tutorials, and resources for machine learning using the Ruby programming language.
A Ruby library for building LLM-powered applications with a unified interface for multiple providers, RAG systems, and AI assistants.
A Ruby gem for building LLM-powered applications with a unified interface for multiple providers, RAG systems, and AI assistants.
A Ruby library implementing the ID3 algorithm for decision tree learning with support for continuous and discrete datasets.
A Ruby library that enables direct calling of Python functions and modules with automatic type conversion.
A Ruby machine learning library with a Scikit-Learn-like interface for classification, regression, clustering, and dimensionality reduction.
A Ruby library for building and serving predictive models with support for PMML and integration with Python and R models.
A lightweight feedforward neural network with resilient backpropagation (Rprop), implemented in pure Ruby with no external dependencies.
A collection of neuroevolution experiments for reinforcement learning control problems using unsupervised learning feature extractors.
A Ruby interface to XGBoost, providing high-performance gradient boosting for machine learning tasks.
A Ruby implementation of k-means clustering with k-means++ initialization, silhouette scoring, and multiple runs for optimal results.
A Ruby gem providing high-performance gradient boosting with LightGBM for machine learning tasks.
Ruby interface to LIBLINEAR for machine learning classification and regression tasks using SWIG bindings.
A Ruby gem for scoring predictive models using PMML, supporting decision trees, naive Bayes, logistic regression, random forests, and gradient boosted trees.
A JRuby gem providing Ruby interfaces for Weka's machine learning and data mining algorithms.
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