January 2019
Intermediate to advanced
294 pages
6h 43m
English
Sometimes, one machine learning model is not good enough for a certain scenario or use case as it might not give you the desired accuracy, recall, and precision. Hence, multiple learning models—or an ensemble of models captures the pattern of the data and gives better output.
As an example, let's say we are trying to decide on a place where we would like to go in the summer. Typically, if we are planning for a trip, the suggestions for the place pours in from all corners. That is, these suggestions might come from our family, websites, friends, and travel agencies, and then we have to decide on the basis of a good experience that we had in the past:
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