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Machine Learning Algorithms
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Module 2
Tree-Based Models and Ensembles
1
Entropy and Gini Impurity: Measuring Node Impurity for Tree Splits
Explain the formulas for Entropy and Gini Impurity, and demonstrate their use in measuring node impurity for tree splits.
2
Ensemble Learning: Bagging & Boosting
Define Ensemble Learning and explain the core ideas of Bagging and Boosting.
3
Examining Ensemble Methods: Random Forests and Gradient Boosting in Assessments
Describe how common ensemble methods like Random Forests and Gradient Boosting are presented in exam questions.
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Machine Learning Fundamentals
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Advanced Supervised Models