Ensemble methods are powerful techniques that combine multiple weak learners to improve predictive performance. One popular ensemble method is bagging, which aggregates the predictions of multiple models trained on subsamples of the data. Random Forest, a widely used algorithm, employs bagging with decision trees to produce robust and scalable models. Introduction In this blog post,…