[PDF.51cr] Matrix and Tensor Factorization Techniques for Recommender Systems (SpringerBriefs in Computer Science)

Matrix and Tensor Factorization Techniques for Recommender Systems (SpringerBriefs in Computer Science)

[PDF.qw42] Matrix and Tensor Factorization Techniques for Recommender Systems (SpringerBriefs in Computer Science)

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 | #880394 in Books |  2017-02-06 |  2017-02-06 | Original language:English | PDF # 1 |  9.25 x.26 x6.10l,.0 | File type: PDF | 102 pages

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||From the Back Cover||This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender systems, such as Singular Value Decompos

This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender systems, such as Singular Value Decomposition (SVD), UV-decomposition, Non-negative Matrix Factorization (NMF), etc. and describes in detail the pros and cons of each method for matrices and tensors. This book provides a detailed theoretical mathematical background of ma...

You easily download any file type for your gadget.Matrix and Tensor Factorization Techniques for Recommender Systems (SpringerBriefs in Computer Science)   |  Panagiotis Symeonidis, Andreas Zioupos. Which are the reasons I like to read books. Great story by a great author.

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