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Handbook of big data /

"Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Άλλοι συγγραφείς: Bühlmann, Peter, Drineas, Petros, Kane, Michael, Laan, M. J. van der
Μορφή: Printed Book
Έκδοση: Boca Raton: CRC Press, c2016
Σειρά:Chapman & Hall/CRC handbooks of modern statistical methods.
Θέματα:
Διαθέσιμο Online:cover image
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020 |a 9781482249071 
020 |z 9781482249088 (PDF ebook) 
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245 0 0 |a Handbook of big data /  |c edited by Peter Bühlmann, Petros Drineas, Michael Kane, Mark van der Laan. 
260 |a Boca Raton:  |b CRC Press,  |c c2016 
300 |a xvi, 464 pages :  |b illustrations (some color) ;  |c 26 cm. 
650 0 |a Big data 
700 1 |a Bühlmann, Peter, 
700 1 |a Drineas, Petros, 
700 1 |a Kane, Michael 
700 1 |a Laan, M. J. van der, 
942 |2 ddc  |c REF 
490 1 |a Chapman & Hall/CRC handbooks of modern statistical methods 
500 |a "Chapman & Hall book." 
504 |a Includes bibliographical references and index. 
505 0 |a The advent of data science: some considerations on the unreasonable effectiveness of data / Richard J.C.M. Starmans -- Big-n versus big-p in big data / Norman Matloff -- Divide and recombine: approach for detailed analysis and visualization of large complex data / Ryan Hafen -- Integrate big data for better operation, control, and protection of power systems / Guang Lin -- Interactive visual analysis of big data / Carlos Scheidegger -- A visualization tool for mining large correlation tables: the association navigator / Andreas Buja, Abba M. Krieger, and Edward I. George -- High-dimensional computational geometry / Alexandr Andoni -- IRLBA: fast partial singular value decomposition method / James Baglama -- Structural properties underlying high-quality randomized numerical linear algebra algorithms / Michael W. Mahoney and Petros Drineas -- Something for (almost) nothing: new advances in sublinear-time algorithms / Ronitt Rubinfeld and Eric Blais -- Networks / Elizabeth L. Ogburn and Alexander Volfovsky -- Mining large graphs / David F. Gleich and Michael W. Mahoney -- Estimator and model selection using cross-validation / Iván Díaz -- Stochastic gradient methods for principled estimation with large datasets / Panos Toulis and Edoardo M. Airoldi -- Learning structured distributions / Ilias Diakonikolas -- Penalized estimation in complex methods / Jacob Bien and Daniela Witten -- High-dimensional regression and inference / Lukas Meier -- Divide and recombine: subsemble, exploiting the power of cross-validation / Stephanie Sapp and Erin LeDell -- Scalable super learning / Erin LeDell -- Tutorial for causal inference / Laura Balzer, Maya Petersen, and Mark van der Laan -- A review of some recent advances in causal inference / Marloes H. Maathuis and Preetam Nandy -- Targeted learning for variable importance / Sherri Rose -- Online estimation of the average treatment effect / Sam Lendle -- Mining with inference: data-adaptive target parameters / Alan Hubbard and Mark van der Laan. 
520 |a "Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical and computing ideas that can be readily applied in research and practice"-- 
655 7 |a Handbooks and manuals.  |2 lcgft 
830 0 |a Chapman & Hall/CRC handbooks of modern statistical methods. 
856 |3 cover image  |u http://coverart.oclc.org/ImageWebSvc/oclc/+-+018240484_140.jpg?SearchOrder=+-+OT,OS,TN,GO,FA 
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