Applications of Unsupervised learning using k-means cluster or Association rules

Question

I have been looking into some applications for unsupervised learning, but have only found some hypothetical applications on the internet, for example unsupervised learning could be used for, say, fraud detection. For example, for supervised learning you have the instant physician which is being implemented in the real world. However, for unsupervised learning, the applications seem to be hypothetical, thus are actually being implemented or are they just hypothetical?

Answer 1

There are lots of applications of unsupervised learning and there are various techniques that help us achieve these applications.I will brief out some of them

1) Image Segmentation - wherein you divide your image into different regions and then cluster them to objectify them.

2) Netflix movie recommendation system wherein those movies which are watched by a user are put into one cluster. Here unsupervised learning plays a important role in determining those movies and then recommending other such/similar movies to that user.

3) Amazon shopping where similar users based on their shopping history, amount paid for items, visiting particular type of items are all put in one clusters which help these giants to look into these factors and then recommend only those things to you.

To achieve these and others one requires unsupervised learning based techniques. Some techniques like k-means, hierarchical clustering, Density based clustering are extensively used for real- world applications.

These are just few of the many applications of unsupervised learning.

Hope this clarify.