Learning Path

Supervised Learning Fundamentals → Ensemble Project: Comparative Analysis

This advanced graduate-level path equips ML practitioners with a deep understanding of ensemble methods, from foundational concepts to state-of-the-art implementations. Learners will master bagging, boosting, and stacking, and apply them using modern libraries like XGBoost, LightGBM, and CatBoost to achieve superior model accuracy.