Training Clinically Actionable Machine Learning Models скачать в хорошем качестве

Training Clinically Actionable Machine Learning Models

You've trained your ML model and the accuracy is high. Time to celebrate? Not so fast. The most dangerous models aren't the ones that perform poorly; they're the ones that seem to perform brilliantly but crumble in production. In this talk, I pull back the curtain on why this happens. This disconnect is almost always caused by methodological shortcuts (some intentional, some accidental) that create a false sense of security. I'll identify these critical errors, like data leakage and flawed validation, and provide a framework of disciplined practices to ensure the performance you calculate translates to genuine, real-world success.