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Mining of Massive Datasets

Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman




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 | #78857 in Books |  2014-12-29 | Original language:English | PDF # 1 |  9.72 x1.18 x6.85l,2.18 | File type: PDF | 476 pages

||4 of 4 people found the following review helpful.| A wonderful reference book|By Sneha|This book is a delight for anyone who deals with practical Data Mining applications. Over the past few years, I have gathered bits and pieces of knowledge from various sources about machine learning, Map Reduce programming paradigm, design and analysis of algorithms, information retrieval, etc. But this book serves to tie it all together bea|About the Author|Jure Leskovec is Assistant Professor of Computer Science at Stanford University. His research focuses on mining large social and information networks. Problems he investigates are motivated by large scale data, the Web and on-line media. This re

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the map-...

You easily download any file type for your device.Mining of Massive Datasets   |  Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman. Just read it with an open mind because none of us really know.

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