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Complete all chapters to get certificate

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Basic Principles of Building Ensemble Models

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What is an ensemble? How are ensembles different from standard machine-learning models? What are the types of ensembles? Let's consider the answers to these questions.

What is Ensemble of Models?

Bagging Models

Boosting Models

Stacking Models

Commonly Used Bagging Models

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Let's consider some commonly used bagging ensemble models, the features of their use, and also apply some of them to solve real-life tasks.

Bagging Classifier

Challenge: Solving Task Using Bagging Classifier

Bagging Regressor

Challenge: Solving Task Using Bagging Regressor

Random Forest

Challenge: Determining Feature Importances Using Random Forest

ExtraTrees

Commonly Used Boosting Models

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The mechanism of work of boosting models differs from bagging models. Now we will explore these distinctions, gain insights into utilizing model boosting for problem-solving, and illustrate its functionality through practical demonstrations.

AdaBoost Classifier

Challenge: Solving Task Using AdaBoost Classifier

Challenge: Solving Task Using AdaBoost Regressor

Gradient Boosting

XGBoost

Challenge: Solving Task Using XGBoost

Commonly Used Stacking Models

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Let's consider some commonly used stacking ensemble models, the features of their use, and also apply some of them to solve real-life tasks.

Stacking Classifier

Challenge: Solving Task Using Stacking Classifier

Challenge: Solving Task Using Stacking Regressor

Using Ensembles As Base Models

Course Summary