Unsupervised Learning

In unsupervised learning, we are provided with a dataset and nothing else. There is no outputs, parameters or anything to distinguish the given data. Our aim is to let the machine to learn or create a grouping/classification on its own.
Unsupervised learning is comparatively difficult with respect to supervised learning.
Consider social networking sites, based on our actions they are filling our feed with posts/media that we would prefer, suggests people we want to follow and a lot of things. These kinds of solutions are done using unsupervised learning.

In the figure, social media users are grouped by machine based on some factors which are unknown to the programmer. This could be a simple example of unsupervised learning.


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