January 2019
Intermediate to advanced
390 pages
9h 16m
English
In our daily life, when we have to make a decision, we take guidance not from one person, but from many individuals whose wisdom we trust. The same can be applied in ML; instead of depending upon one single model, we can use a group of models (ensemble) to make a prediction or classification decision. This form of learning is called ensemble learning.
Conventionally, ensemble learning is used as the last step in many ML projects. It works best when the models are as independent of one another as possible. The following diagram gives a graphical representation of ensemble learning:

The training of different models can take ...
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