Solid refresher from KDNuggets on the three issues that quietly wreck ML models: overfitting, class imbalance, and feature scaling. Nothing groundbreaking, but the kind of practical checklist every practitioner should revisit before debugging for hours
Solid refresher from KDNuggets on the three issues that quietly wreck ML models: overfitting, class imbalance, and feature scaling. Nothing groundbreaking, but the kind of practical checklist every practitioner should revisit before debugging for hours 🔧
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