April 2017
Intermediate to advanced
532 pages
12h 39m
English
book
Machine Learning with Spark - Second Edition
by Rajdeep Dua, Brian O'Neill, Stephen Boesch, Manpreet Singh Ghotra, Nick Pentreath
Content preview from Machine Learning with Spark - Second Edition
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Matrices in machine learning
Matrices are used as mathematical objects to represent images, datasets for real world machine learning applications like a face or text recognition, medical imaging, principal component analysis, numerical accuracy, and so on.
As an example, eigen decomposition is explained here. Many mathematical objects can be understood better by breaking them into constituent parts, or by finding properties which are universal.
Like when integers are decomposed into prime factors, matrix decomposition is called eigen decomposition, where we decompose a matrix into eigenvectors and eigenvalues.
Eigenvector v of a matrix A is such that multiplication by A alters only the scale of v, as shown next:
Av = λv
The scalar λ is known ...
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