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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...
| מחברים אחרים: | , , , |
|---|---|
| פורמט: | Printed Book |
| סדרה: | Chapman & Hall/CRC handbooks of modern statistical methods
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| נושאים: |
| LEADER | 03308cam a22002417i 4500 | ||
|---|---|---|---|
| 999 | |c 214833 |d 214833 | ||
| 020 | |a 1482249073 | ||
| 020 | |a 9781482249071 | ||
| 082 | 0 | 4 | |a 005.7 |b HAN |
| 245 | 0 | 0 | |a Handbook of big data / |c edited by Peter Bühlmann, Petros Drineas, Michael Kane, Mark van der Laan. |
| 300 | |a xvi, 464 pages : |b illustrations (some color) ; | ||
| 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"-- | ||
| 650 | 0 | |a Big data |v Handbooks, manuals, etc. | |
| 700 | 1 | |a Bühlmann, Peter, | |
| 700 | 1 | |a Drineas, Petros, | |
| 700 | 1 | |a Kane, Michael | |
| 700 | 1 | |a Laan, M. J. van der, | |
| 942 | |c BK | ||
| 952 | |0 0 |1 0 |4 0 |6 005_700000000000000_HAN |7 0 |9 228664 |a DFS |b DFS |d 2019-12-02 |l 0 |o 005.7 HAN |p DFS4231 |r 2019-12-02 |w 2019-12-02 |y BK | ||