A practical framework for AI-Assisted Research in Mathematics and Machine Learning

A collection of notes on Data Science

Experiment task scheduling made easy.

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

LLM agents as your hyperparameter optimizer.

Learn what AI skills are and how to design, structure, and use them in real-world agent systems.

🔨 Kyoko is the all-in-one, fully local tool for debugging and improving your AI agents.

Learn AI and LLMs from scratch using free resources

An ML engineering plugin for your coding agents.

Curated list of AutoResearch use cases with optimization traces and open source implementations

The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai

🤖 AI Agent-driven Kaggle competition workflow. Battle-tested patterns for score stabilization, submission troubleshooting, kernel workflows, and spec-driven development.

MCP server for spatial transcriptomics analysis through natural language interfaces.

Claude Code, Codex, and multi-agent configuration system: principles, hooks, skills, and workflow patterns for AI-assisted development

Umbrella package for SciTeX — reproducible science from raw data to manuscript

Learn it. Build it. Ship it for others.

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.

Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.

YC (S26) | Open Computer History | Record your screen continuously locally and provide context to your agents (Claude, Codex, Openclaw, Hermes, Runner...)

🔥 An autonomous AI agent that runs your deep learning experiments 24/7 while you sleep. Zero-cost monitoring, Leader-Worker architecture, constant-size memory.

Shared Single-file memory layer for all your agents, sub mili-second RAG over text, photo and video on Apple Silicon.. No Server. No API. One File. Pure Swift

A universal, industry-neutral taxonomy of cognitive core skills (perception, memory, reasoning, planning, action, verification, learning, governance) for LLMs, SLMs, AI agents, and world models — with schemas, 159 skill cards, benchmarks, and CI.

High-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes. Build, debug, and scale LLM workflows with 13+ model providers, 8+ vector databases, and agent orchestration, all from your IDE. Includes VS Code extension, TypeScript/Python SDKs, and Docker deployment.