Ensembling, which is super-famous among ML practitioners, can be well-understood through a simple real-world, non-ML example.

Assume that you have applied for a job in a very reputable corporate organization and you have been called for an interview. It is unlikely you will be selected for a job just based on one interview with an interviewer. In most cases, you will go through multiple rounds of interviews with several interviewers or with a panel of interviewers. The expectation from the organization is that each of the interviewers is an expert on a particular area and that the interviewer has evaluated your fitness for the job based on your experience in the interviewers' area of expertise. Your selection for the job, of course, depends on consolidated feedback from all of the interviewers that talked to you. The organization deems that you...