The AI Trading Paradigm Shift: How Machine Learning and Backtesting Evolved a Python Bot

This project demonstrates how machine learning and rigorous backtesting transform simple signal-based trading systems into production-grade automated traders. By documenting 5 months of iteration—expanding from 9 to 12 strategies while adding ML scoring and partial take-profit logic—the author reveals the practical engineering required to build reliable trading bots that survive audits and real-money testing. Open-sourced under MIT, the project provides developers with a reusable template for building AI-native trading systems.