Toolkit to get started with supervised machine learning
A visualization of popular supervised learning algorithms using [JSMLT](https://github.com/jsmlt/jsmlt).
Machine learning tools
A conversational AI-driven telecom multi-agent system for managing call balances, push notifications, marketing, targeting, and sales.
Find meaning in the web.
Dispatcher contains a Softmax learner initially used for auto-active-learning down-sampling and a ML confusion-matrix evaluator on intent classification models.
A machine learning library implementing common algorithms for unsupervised and supervised learning.
Generic build of Mozilla's PDF.js library.
Self-Optimizing Neural Architecture (SONA) - Runtime-adaptive learning with LoRA, EWC++, and ReasoningBank for LLM routers and AI systems. Sub-millisecond learning overhead, WASM and Node.js support.
Self-learning vector memory for AI agents — single-file .rvf cognitive container with HNSW search, episodic Reflexion memory, causal graph + Cypher, 9 RL algorithms, Thompson Sampling bandit, 41 MCP tools, hybrid (BM25 + dense) retrieval, GNN attention. 1
Hanseol - OpenAI-Compatible Coding Agent
Codex CLI integration for Ruflo (claude-flow) - OpenAI Codex platform adapter
Cross validation utility for mljs classifiers
TensorFlow layers API in JavaScript
Node.js FastText
AWS SDK for JavaScript Machine Learning Client for Node.js, Browser and React Native
List of ML tasks for huggingface.co/tasks
Quantity parsing, formatting and conversions for iModel.js
Provides a smooth, zoomable user interface for HTML/Javascript.
A factory for kernel functions
Production-ready AI agent orchestration platform with 66 specialized agents, 213 MCP tools, ReasoningBank learning memory, and autonomous multi-agent swarms. Built by @ruvnet with Claude Agent SDK, neural networks, memory persistence, GitHub integration,
Build cross platform desktop apps with JavaScript, HTML, and CSS
Ultra-fast MicroLoRA adaptation for WASM - rank-2 LoRA with <100us latency for per-operator learning
Exploratory Data Analysis Tools
Supervised learning is the machine learning task of inferring a function from labeled training data. A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.
Implements supervised Bayesian structure learning, as well as extra tools to help train a Bayesian net using ActiveRecord data
A library for solving Supervised Learning (regression & classification) problems
A port of the brain.js library, implementing a multilayer perceptron - a neural network for supervised learning.
Create K-fold splits from data files and assist in training and testing (useful for cross-validation in supervised machine learning)
SHALMANESER - SHALlow seMANtic parSER. This package provides a toolbox for Semantic Role Labeling (SRL). SHALMANESER uses supervised learning algorithms to assing semantic classes and roles to raw texts. It is paradigm agnostic, i.e. it can handle any role-semantic schema (FrameNET, PropBank etc.) and use any set of word senses (e.g. WordNet synsets). SHALMANESER emerged as part of the SALSA Project at the University of Saarbrücken.
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