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This project is available as an internship opportunity with HPCC Systems this summer.

Find out more about the HPCC Summer Internship Program.
Deadline for machine learning project proposals - Friday March 25th 2016

Curious about other projects we are offering? Take a look at our Ideas List
Deadline for non-machine learning project proposals - Friday April 15th 2016


Project Description
SVD has many applications. For example, SVD could be applied to natural language processing for latent semantic analysis (LSA). LSA starts with a matrix whose rows represent words, columns represent documents, and matrix values (elements) are counts of the word in the document. It then applies SVD to the input matrix, and uses a subset of most significant singular vectors and corresponding singular values to map words and documents into a new space, called ‘latent semantic space’, where documents are placed near each other measured by co-occurrence of words, even if those words never co-occurred in the training corpus.

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