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I am very new to machine learning. I just understand dimesionality reduction from here

I am trying to understand this paper. Here they use Singular value decomposition to reduce dimension. Can anybody explain in very simple language what is singular value decomposition?I do not need the steps for doing it, i just want to feel the output and it's relation to input matrix. And how it can be used in dimensionality reduction.

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    Welcome to our site. Often it is most useful to you when you begin with a [search](http://stats.stackexchange.com/search?q=svd+dimension+reduction). – whuber Nov 14 '15 at 19:23
  • I found that before but wanted something that is easily explained with some practical example. i found http://www.cs.carleton.edu/cs_comps/0607/recommend/recommender/svd.html this . This was really helpfull. Thanks @whuber – user3363813 Nov 14 '15 at 23:34

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