Beyond Deployment: Continuously Adding Features to Drive Marginal Gains in Models

Mark Fukson

Machine learning models are never truly “done.” As data evolves, so should the models that rely on it. But how can we ensure continuous improvement without costly retraining or manual intervention? In this talk, we introduce an automated pipeline designed to incrementally enhance model performance by systematically testing and integrating new features.