Fixing Classical Models – Diagnosis & Regularization

In this course, learners will improve a poorly performing classical ML model using core diagnostic and regularization techniques. The model starts off weak, and learners fix it step by step through evaluation, regularization, capacity tuning, and early stopping. All models are built using scikit-learn or XGBoost.