AI Engineer Interview

Sharpen your understanding of the models and math powering modern ML systems. This quiz covers ensemble methods (bagging, boosting, random forests, XGBoost), neural network architectures and regularization techniques (dropout, L1/L2, batch normalization), and model evaluation strategies (cross-validation, precision-recall, ROC-AUC, bias-variance tradeoff). Ideal for practitioners moving beyond basic ML into deeper theory and applied techniques used in real-world systems.