As a newbie, I have been going through mutiple models of machine learning & came across Bagging (Bootstrap Aggregating) and Random Forest. However, I fail to understand the exact difference between thse two models. Could any of you explain it with any easy example, in a way to understand by a beginner ? A simple example shoudl be enough. Probably you can show, in a particular dataset, how these 2 models will produce 2 different results. Thanks in advance.