Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

Mining of Massive Datasets, EPUB eBook

Mining of Massive Datasets EPUB

EPUB

Please note: eBooks can only be purchased with a UK issued credit card and all our eBooks (ePub and PDF) are DRM protected.

Description

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-reduce framework, an important tool for parallelizing algorithms automatically.

The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing.

Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets and clustering.

This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction.

Information

Other Formats

Information