A JavaScript library for escaping CSS strings and identifiers while generating the shortest possible ASCII-only output.
Matrix manipulation and computation library
For ruby and ruby on rails
Get the maximum value in an array
Various method to process spectra
Get the minimum value in an array
JavaScript implementation of the XORSHIFT-ADD (XSadd) pseudo random number generator
Rescale an array into a range
Compute the euclidean distance between two vectors
Generates markdown API documentation from jsdoc annotated source code
Web Assembly streaming Opus decoder with Machine Learning enhancements
Ruby SemVer in TypeScript.
Convention over configuration for using Vite in Ruby apps
Find the nearest point to a sample point
Choose randomly from a selection of elements
Like ruby's abbrev module, but in js
Get the average value in an array
Ruby grammar for tree-sitter
prettier plugin for the Ruby programming language
K-Means clustering
Distance and similarity functions to compare vectors
Get the average value in an array
WebSocket framework for Ruby on Rails.
Autogenerate READMEs tables and OpenAPI schemas for Helm Charts
ML Ruby are the ruby bindings for the open source peer 2 peer software MLDonkey. This is the first part of an alternative to the official web GUI written in Ruby On Rails.
A ruby machine learning gem
This Ruby gem leverages Machine Learning(ML) techniques to make predictions(forecasts) and classifications in various applications. It provides capabilities such as predicting next month's billing, forecasting upcoming sales orders, identifying patient's potential findings(like Diabetes), determining user approval status, classifying text, generating similarity scores, and making recommendations. It uses Python3 under the hood, powered by popular machine learning techniques including NLP(Natural Language Processing), Decision Tree, K-Nearest Neighbors and Logistic Regression, Random Forest and Linear Regression algorithms.
Official AWS Ruby gem for AWS Clean Rooms ML. This gem is part of the AWS SDK for Ruby.
AI4R is a lightweight, educational Ruby library featuring clean implementations of core machine learning and AI algorithms—such as decision trees, neural networks, k-means, genetic algorithms, and even a bit size Transformers architecture covering encoder, decoder, and seq2seq variations. Designed with simplicity and clarity in mind, this library is ideal for students, educators, and developers who want to understand these algorithms line by line. With no external dependencies, no GPU support, and no production overhead, AI4R serves as a practical and transparent way to explore the foundations of AI in Ruby. It is a long-maintained open-source effort to bring accessible, hands-on machine learning to the Ruby community.
A ruby based library of Maching Learning (ML) algorithms
Ruby library for integrating with the 42Floors MLS
Algorithms for machine learning and artificial intelligence in Ruby.
Lancelot provides a Ruby-native interface to Lance, enabling efficient storage and search of multimodal data including text, vectors, and more.
A Ruby-native interface for fine-tuning machine learning models, starting with image classification using SigLIP2
Ruby-only adapter that adds post-quantum ML-DSA JWS signing and AKP JWK/JWKS helpers to ruby-jwt, backed by pq_crypto.
Adds ML-DSA-44, ML-DSA-65, and ML-DSA-87 post-quantum signature algorithms to the ruby-jwt ecosystem, with optional hybrid EdDSA + ML-DSA mode. Uses liboqs via FFI.