New York: Springer, 2017. — 532 p.This essential guide to a broad spectrum of big data analytics in cross-disciplinary applications focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discovery from big data. The primary audience will be statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
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