Mensys Online Shop

Mining the Social Web - eBook (PDF)

Categorie:Algemeen - Digitale Boeken (eBoeken) Van:O'REILLY MEDIA
Auteur(s):Russell, Matthew A.Bladzijden:448
Publicatie-jaar:2013 

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.

Mining the Social Web - eBook (PDF)

Selecteer een of meer artikelen en klik dan op Bestellen. Aantallen kunnen op de volgende blz. gewijzigd worden.
 Mining the Social Web
Partnr.OmschrijvingEuro *Euro incl. BTW 
9781449368227 Mining the Social Web Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More 2ed. PDF26.8632.50

Alle prijzen zijn in Euro excl. BTW (21%, voor boeken 6%) en excl. verzendkosten.
Verzenden is gratis bij orders boven de 20 euro in Nederland, daaronder 5 euro excl. BTW.

E-mail of bel 085 40 19 16 0 voor licenties, upgrades en andere vragen.

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.