Goal: Have a working dataset + baseline XGBoost model + local API. - Set up project repo + Python environment. - Generate synthetic bootstrap dataset. - Do light EDA. - Train baseline XGBoost classifier. - Save model + inspect feature importance. - Build minimal FastAPI endpoint /recommend. - Test with sample JSON input via curl or Postman. - EOW deliverable: Local API that takes input → returns EVOLVE / GROW / OVERACHIEVE with confidence.