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Mining The Social Web Data Mining Facebook Twitter Linkedin Google Github And More 2nd Edition Matthew A Russell

  • SKU: BELL-4421070
Mining The Social Web Data Mining Facebook Twitter Linkedin Google Github And More 2nd Edition Matthew A Russell
$ 31.00 $ 45.00 (-31%)

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Mining The Social Web Data Mining Facebook Twitter Linkedin Google Github And More 2nd Edition Matthew A Russell instant download after payment.

Publisher: O'Reilly Media
File Extension: PDF
File size: 21.05 MB
Pages: 448
Author: Matthew A. Russell
ISBN: 9781449367619, 9781449368203, 1449367615, 1449368204
Language: English
Year: 2013
Edition: 2

Product desciption

Mining The Social Web Data Mining Facebook Twitter Linkedin Google Github And More 2nd Edition Matthew A Russell by Matthew A. Russell 9781449367619, 9781449368203, 1449367615, 1449368204 instant download after payment.

How can you tap into the wealth of social web data to discover who’s making connections with whom, what they’re talking about, and where they’re located? With this expanded and thoroughly revised edition, you’ll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs.
• Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites
• Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data
• Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects
• Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit
• Take advantage of more than two-dozen Twitter recipes, presented in O’Reilly’s popular "problem/solution/discussion" cookbook format
The example code for this unique data science book is maintained in a public GitHub repository. It’s designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.

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