Part 1/11:
Understanding Ensemble Learning: Bagging and Boosting
In the ever-evolving landscape of machine learning, two prominent techniques stand out: bagging and boosting. Both are types of ensemble learning, a method that combines multiple models to improve predictive accuracy and reliability. This article will delve into the essence of ensemble learning, exploring the distinctions and implementations of both bagging and boosting, their advantages, and how they shape the machine learning field.