Add AI Trading System with Adversarial Debate to Machine Learning

[alex-jb]

Adds Orallexa to the Machine Learning section — an end-to-end AI trading system that demonstrates:

• 9 ML models (Random Forest, XGBoost, EMAformer, DDPM Diffusion, PPO RL, GNN, etc.) scored and ranked by Sharpe ratio
• Adversarial debate pipeline — Bull AI argues for, Bear AI argues against, Judge AI decides with evidence
• Full-stack implementation — Python backend (FastAPI) + Next.js 16 dashboard + desktop agent
• 277 automated tests, walk-forward evaluation, paper trading via Alpaca
• Live demo available at https://orallexa-ui.vercel.app

Repository: https://github.com/alex-jb/orallexa-ai-trading-agent

This is a practical, project-based learning resource that covers ML pipelines, LLM integration, real-time dashboards, and trading system architecture.

[tuvtran]

Thanks for sharing your project — it looks like an ambitious piece of work. However, this list is for free project-based tutorials that walk readers through building something themselves, and a project showcase repo (even an impressive one) doesn't fit that scope. If you ever write a step-by-step tutorial on building such a system, we'd be glad to consider it.