What you’ll learn
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Solid understanding of decision trees, bagging, Random Forest and Boosting techniques in R studio
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Understand the business scenarios where decision tree models are applicable
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Tune decision tree model’s hyperparameters and evaluate its performance.
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Use decision trees to make predictions
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Use R programming language to manipulate data and make statistical computations.
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Implementation of Gradient Boosting, AdaBoost and XGBoost in R programming language