58. Explain ensemble learning, and how does it work?
The goal when applying Data Science and Machine Learning to build models is to create a model that can understand the underlying trends in the training data and make accurate predictions or classifications. However, some datasets are exceedingly complex, and understanding the underlying trends in these datasets might be difficult for a single model. Sometimes in the attempt to boost performance, multiple unique models are merged and this method is known as ensemble learning.
