Open-source alternatives to Dn2a Javascript

ConvNetJS is a JavaScript deep learning library and neural network training engine designed for client-side machine learning. It functions as a framework for building, training, and running convolutional neural networks directly within a web browser without the need for a backend server. The library specializes in image recognition and pattern analysis using convolutional and pooling layers. It enables the creation of models for classification and regression tasks, as well as the development of reinforcement learning agents that optimize behavior through trial and error in simulated environme

OCR in Javascript via Emscripten

Brain is a JavaScript library for building, training, and running feed-forward neural networks. It implements a multilayer perceptron model designed for pattern recognition and function approximation. The library includes a standalone inference engine that converts trained models into portable JavaScript functions. This allows predictions to be executed in browser or Node.js environments without requiring the original library dependencies. The system supports persistent model management through JSON serialization for saving and loading network weights. It also provides a streaming mechanism

Aye Chat: AI-powered terminal workspace

ANEE is an experimental dynamic inference wrapper for pretrained Transformer language models (currently GPT-2). Instead of always running all layers, ANEE exposes an energy_budget and performs early exit inside the model’s forward pass.

Open coding agent, provider agnositc.

FinRL is a financial reinforcement learning framework and quantitative trading library. It provides a specialized system for developing, training, and simulating autonomous agents designed to automate financial trading and portfolio management. The project serves as an automated portfolio optimizer and financial market simulator. It enables the creation of decision-making policies to balance asset allocations, maximize potential returns, and minimize financial risk through reinforcement learning. The framework includes capabilities for financial market data engineering, algorithmic trading s

Reinforcement learning resources curated

Machine Learning Yearning book by 🅰️𝓷𝓭𝓻𝓮𝔀 🆖

A list of awesome tools, ideas, prompt engineering tools, colabs, models, and helpers for the prompt designer playing with aiArt and image synthesis. Covers Dalle2, MidJourney, StableDiffusion, and open source tools.

Agentset MCP Server - Build RAG with Agentic superpowers

AI agents in Go — Temporal for durable, crash-resilient execution or run in-process with zero setup. OpenAI, Anthropic, Gemini, tools, MCP, A2A, RAG, conversations, AG-UI, streaming, sub-agents & human-in-the-loop.

Let AI agents message, watch, and spawn each other across terminals. Claude Code, Codex, Antigravity CLI, Cursor CLI, OpenCode, Kilo, Pi, Kimi

OpenCode is a framework for orchestrating autonomous AI agents within development environments. It provides a multi-tiered architecture where primary assistants manage user interaction while specialized subagents handle specific tasks like planning, research, and code generation. The system includes a comprehensive command-line interface for managing these workflows, configuring agent behavior, and defining custom tools or commands through metadata-rich files. The platform features a modular plugin system and extensive integration support, including standardized protocols for connecting local

Zsh plugin that integrates Claude Code CLI into your shell. Chat with Claude and execute AI-generated commands directly from your terminal prompt

acl-release-shield: https://img.shields.io/badge/version-53.1.0-green acl-release: https://github.com/ARM-software/ComputeLibrary/releases/v53.1.0

Stable Diffusion Web UI is a browser-based interface designed for managing text-to-image generation tasks. It provides a centralized dashboard for controlling generative processes, including native support for multi-stage model architectures to facilitate high-quality image refinement. The platform distinguishes itself through granular control over the generation process, offering tools for precise parameter management and advanced prompt engineering. Users can customize generation styles and capabilities by integrating external model-extension formats, such as textual inversions, low-rank ad

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

A curated list of community detection research papers with implementations.

A collection of research papers on decision, classification and regression trees with implementations.

A curated list of data mining papers about fraud detection.

A curated list of gradient boosting research papers with implementations.

A collection of important graph embedding, classification and representation learning papers with implementations.

A curated list of Monte Carlo tree search papers with implementations.

Lightweight AI agent runtime for Go. Define multi-agent crews in YAML, run them with goroutines and channels, and let the runtime handle scheduling, parallelism, retries, and observability — without leaving the Go ecosystem.