[PDF.90ei] Sublinear Algorithms for Big Data Applications (SpringerBriefs in Computer Science)

Sublinear Algorithms for Big Data Applications (SpringerBriefs in Computer Science)

[PDF.ql94] Sublinear Algorithms for Big Data Applications (SpringerBriefs in Computer Science)

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 | #5328182 in Books |  2015-08-20 |  2015-08-20 | Original language:English | PDF # 1 |  9.25 x.23 x6.10l,.35 | File type: PDF | 85 pages

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||0 of 0 people found the following review helpful.| Nice introduction!|By Debasish Ghosh|The book does a good job of introducing the concepts of sublinear algorithms and then goes into the details of implementing a few use cases in the real world. The best part of the book is the balance between the theory of sublinear algorithms and their implementations.| ||“Wang and Han’s book focuses on sublinear algorithms for processing big data. … For the researcher, this book also shows that there is room for improvement and new discoveries in this flourishing area. … The book is thus recommended

The brief focuses on applying sublinear algorithms to manage critical big data challenges. The text offers an essential introduction to sublinear algorithms, explaining why they are vital to large scale data systems. It also demonstrates how to apply sublinear algorithms to three familiar big data applications: wireless sensor networks, big data processing in Map Reduce and smart grids. These applications present common experiences, bridging the theoretical advances of s...

You easily download any file type for your device.Sublinear Algorithms for Big Data Applications (SpringerBriefs in Computer Science)   |  Dan Wang, Zhu Han.Not only was the story interesting, engaging and relatable, it also teaches lessons.

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