[PDF] Techniques and Environments for Big Data Analysis: Parallel, Cloud, and Grid Computing (Studies in Big Data)

ISBN: 3319275186

Category: Tutorial


Posted on 2017-10-22, by luongquocchinh.

Description



Author: Mishra, B.S.P., Dehuri, S., Kim, E., Wang, G.-N. | Category: Computer Science | Language: English | Page: 191 | ISBN: 3319275186 | ISBN13: 9783319275185 |

Description: Presents the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it Emphasis is on theoretical advances of Big Data and it’s practices in parallel, cloud, and grid environment Interesting and novel collection useful for researchers and students This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.

DOWNLOADDownload this book
Techniques and Environments for Big Data Analysis: Parallel, Cloud, and Grid Computing (Studies in Big Data).pdf
http://uploaded.net/file/jzhxgi4w

Sponsored High Speed Downloads
7817 dl's @ 2003 KB/s
Download Now [Full Version]
6164 dl's @ 3330 KB/s
Download Link 1 - Fast Download
5950 dl's @ 3897 KB/s
Download Mirror - Direct Download



Search More...
[PDF] Techniques and Environments for Big Data Analysis: Parallel, Cloud, and Grid Computing (Studies in Big Data)

Search free ebooks in ebookee.com!


Links
Download this book

No active download links here?
Please check the description for download links if any or do a search to find alternative books.


Related Books

  1. Ebooks list page : 32642
  2. 2018-01-25[PDF] Applied Biclustering Methods for Big and High-Dimensional Data Using R (Chapman & Hall/CRC Biostatistics Series)
  3. 2018-01-30[PDF] Technology-Supported Environments for Personalized Learning: Methods and Case Studies
  4. 2018-01-16[PDF] Disk-Based Algorithms for Big Data
  5. 2017-11-11[PDF] Rule Based Systems for Big Data: A Machine Learning Approach (Studies in Big Data)
  6. 2017-11-07[PDF] Nonparametric Regression Methods for Longitudinal Data Analysis: Mixed-Effects Modeling Approaches
  7. 2017-10-31[PDF] Computer Simulation Tools for X-ray Analysis: Scattering and Diffraction Methods
  8. 2017-10-16[PDF] Techniques and Sample Outputs that Drive Business Excellence (The Little Big Book Series)
  9. 2017-10-04[PDF] State-Space Methods for Time Series Analysis: Theory, Applications and Software (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
  10. 2018-01-14[PDF] Data Mining, Rough Sets and Granular Computing (Studies in Fuzziness and Soft Computing)
  11. 2018-01-06[PDF] Matte Painting: Environments for Film
  12. 2018-01-06[PDF] Nonlinear Continuum Mechanics for Finite Element Analysis 2nd EDITION
  13. 2018-01-01[PDF] Thin-Layer Chromatography for Binding Media Analysis (Tools for Conservation)
  14. 2017-12-29[PDF] Generalized Linear Models for Insurance Data (International Series on Actuarial Science)
  15. 2017-12-28[PDF] Hard and Soft Computing for Artificial Intelligence, Multimedia and Security (Advances in Intelligent Systems and Computing)
  16. 2017-12-28[PDF] Claudio Moraga: A Passion for Multi-Valued Logic and Soft Computing (Studies in Fuzziness and Soft Computing)
  17. 2017-12-27[PDF] Nonlinear Continuum Mechanics for Finite Element Analysis
  18. 2017-12-17[PDF] Techniques and Methodological Approaches in Breast Cancer Research
  19. 2017-11-25[PDF] Linear Mixed Models for Longitudinal Data (Springer Series in Statistics)
  20. 2017-10-29[PDF] Computers and Society: Computing for Good

Comments

No comments for "[PDF] Techniques and Environments for Big Data Analysis: Parallel, Cloud, and Grid Computing (Studies in Big Data)".


    Add Your Comments
    1. Download links and password may be in the description section, read description carefully!
    2. Do a search to find mirrors if no download links or dead links.

    required

    required, will not be published

    need login

    required

    Not clear? Click here to refresh.

    Back to Top