undrgrnd Cliquez ici Baby ValentinB nav-sa-clothing-shoes nav-sa-clothing-shoes Cloud Drive Photos cliquez_ici nav_HPTV Cliquez ici Acheter Fire Acheter Kindle Paperwhite cliquez_ici Jeux Vidéo Montres soldes Bijoux Soldes
Commencez à lire Mining the Social Web sur votre Kindle dans moins d'une minute. Vous n'avez pas encore de Kindle ? Achetez-le ici Ou commencez à lire dès maintenant avec l'une de nos applications de lecture Kindle gratuites.

Envoyer sur votre Kindle ou un autre appareil

 
 
 

Essai gratuit

Découvrez gratuitement un extrait de ce titre

Envoyer sur votre Kindle ou un autre appareil

Désolé, cet article n'est pas disponible en
Image non disponible pour la
couleur :
Image non disponible
 

Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More [Format Kindle]

Matthew A. Russell
4.0 étoiles sur 5  Voir tous les commentaires (1 commentaire client)

Prix conseillé : EUR 30,60 De quoi s'agit-il ?
Prix livre imprimé : EUR 42,34
Prix Kindle : EUR 19,99 TTC & envoi gratuit via réseau sans fil par Amazon Whispernet
Économisez : EUR 22,35 (53%)

App de lecture Kindle gratuite Tout le monde peut lire les livres Kindle, même sans un appareil Kindle, grâce à l'appli Kindle GRATUITE pour les smartphones, les tablettes et les ordinateurs.

Pour obtenir l'appli gratuite, saisissez votre adresse e-mail ou numéro de téléphone mobile.

Formats

Prix Amazon Neuf à partir de Occasion à partir de
Format Kindle EUR 19,99  
Broché EUR 42,02  
-40%, -50%, -60%, -70%... Découvrez les Soldes Amazon jusqu'au 16 février 2016 inclus. Profitez-en !





Les clients ayant acheté cet article ont également acheté

Cette fonction d'achat continuera à charger les articles. Pour naviguer hors de ce carrousel, veuillez utiliser votre touche de raccourci d'en-tête pour naviguer vers l'en-tête précédente ou suivante.

Descriptions du produit

Présentation de l'éditeur

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.


Détails sur le produit

  • Format : Format Kindle
  • Taille du fichier : 9452 KB
  • Nombre de pages de l'édition imprimée : 448 pages
  • Utilisation simultanée de l'appareil : Illimité
  • Editeur : O'Reilly Media; Édition : 2 (4 octobre 2013)
  • Vendu par : Amazon Media EU S.à r.l.
  • Langue : Anglais
  • ASIN: B00FNBWNLU
  • Synthèse vocale : Activée
  • X-Ray :
  • Word Wise: Non activé
  • Composition améliorée: Non activé
  • Moyenne des commentaires client : 4.0 étoiles sur 5  Voir tous les commentaires (1 commentaire client)
  • Classement des meilleures ventes d'Amazon: n°129.464 dans la Boutique Kindle (Voir le Top 100 dans la Boutique Kindle)

Commentaires en ligne

5 étoiles
0
3 étoiles
0
2 étoiles
0
1 étoiles
0
4.0 étoiles sur 5
4.0 étoiles sur 5
Meilleurs commentaires des clients
4.0 étoiles sur 5 Bon ouvrage - un brin "livre de recettes" 28 septembre 2014
Format:Broché|Achat vérifié
Cet ouvrage propose de découvrir un bon nombre d'outils pour aller à la pèche des données sur les réseaux sociaux. Pas très théorique, plutôt axé sur la découverte des APIs.

Si vous voulez comprendre le pourquoi du comment, allez plutôt voir "Doing Data Science" chez O'Reilly. Si vous voulez mettre les mains dans le cambouis, cet ouvrage est fait pour vous.
Avez-vous trouvé ce commentaire utile ?
Signaler un abus
Commentaires client les plus utiles sur Amazon.com (beta)
Amazon.com: 4.5 étoiles sur 5  58 commentaires
25 internautes sur 25 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Must have if interested in mining social media 10 octobre 2013
Par Bernard Enjolras - Publié sur Amazon.com
Format:Broché
The second edition of Mining the Social Web is not just an update of the previous edition (including Google+, GitHub, and Twitter API 1.1) but a new book. The book has been rethought in its entirety with a focus on pedagogy and practical use of the code. With the help of a virtual machine and IPython notebook (both made available by the author) it is possible to run the code without difficulty. The book includes a Twitter Cookbook section which is very useful if you want to mine Twitter. In my opinion this book is the best introduction to real-world programming in Python. It introduces many concepts and tools related to modern web-programming and data-mining. Additionally it gives you the tools and the code for querying social media APIs and analyzing your data in a meaningful way. Matthew Russell has realized a tour de force with the new edition of this book: introducing advanced programming concepts and tools in a pedagogic, accessible and practical way.
12 internautes sur 12 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Easy to follow, practical, and fun! 5 novembre 2013
Par Greg - Publié sur Amazon.com
Format:Broché
This book is extremely practical and has great code samples. It's easy to follow and fun! If you're interested in mining Twitter data, there is an (large) chapter focused entirely on reproducible code snippets that use the Twitter API.
13 internautes sur 14 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 New Standard in Technical Books 8 novembre 2013
Par Brendon Unland - Publié sur Amazon.com
Format:Broché|Achat vérifié
I have purchased just about every book available on social media data mining/ analytics, including the first edition of this book. What Matthew Russell has done with this second edition is amazing. With the purchase of this book, you get a fully functional virtual machine (available via download on GitHub.) As updates are made to the code for the book, you can easily pull them from GitHub. This eliminates the countless hours you spend downloading, configuring, troubleshooting, wondering if you got the right version of the needed software, etc. Within minutes you can read the book and type the code samples. Actually, the code is already there, you simply enter in some key values and watch the code run. You can then morph the code and see the effects of your changes.

Mining the Social Web is exceptionally well written covering all major social media platforms. Mr. Russell is also very approachable and answers questions very quickly.

I really can't say enough good things about this book and how it sets the bar high for future technical books!
8 internautes sur 8 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Excellent toolkit for Social Data Mining 3 novembre 2013
Par publicprofile - Publié sur Amazon.com
Format:Broché
Great guidebook to acquiring and analyzing data from leading social media sites, including Twittter, Facebook, Google +, LinkedIn and GitHub along with other web tips and tricks. The iPython notebook approach provides turn key like method to run examples and check results in line, which accelerates and reinforces the topics.

Whether you are new to social media API's and want a straightforward way to ramp up learning and discovery of social mining techniques or more seasoned user, this book has it covered. Chapter formats and exercises make it easy to work a variety of topics and are laid out in easy to follow and execute fashion.

Highly recommend, so get the book and get started!
10 internautes sur 11 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 A Hacker's Guide to Social Data Mashups 13 octobre 2013
Par chris725 - Publié sur Amazon.com
Format:Broché
Mining the Social Web v2 is remarkable in terms of its simplicity as well as its depth. The author has focused on reducing friction to learning and executing traditionally difficult topics such as text mining and natural language processing. I already own the first version of MtSW, and between the new topics (LinkedIn, GitHub, Google+) and the new infrastructure (IPython, VirtualBox, etc) this is like a whole new book full of inspiration and ideas. The fact that a lot of this book is a significantly different than the first edition isn't surprising since the topic of the social web is evolving so rapidly.

The reason this is such an important book is that it teaches non-experts to build simple systems for making decisions on data that is constantly up-to-date. It's an end-to-end manual for continuously gathering data (e.g. Twitter API), analyzing data (e.g. Natural Language Processing), and presenting information (e.g. D3). By significantly reducing the barrier to building these systems, Matthew has increased the number of people on the planet that can provide data for making proper decisions . . . and data always beats opinions.

This is one of the rare books that does a great job of introducing deep technical topics AND providing an easy, practical implementation. Unlike a lot of tech books, MtSW makes it trivial to get started through a combination of Vagrant, VirtualBox, IPython Notebook, and GitHub such that you can have all the updated examples up and running within minutes. I'm much more of a practitioner (read: Hacker) than a computer scientist so this is exactly the right amount of technical detail to try out an idea. As an example of technical depth, the coverage of the Twitter API is exactly the proper amount of detail to understand how to pull out tweets and start using the data right away, without slogging through the parts of the API that you'll never need. Better yet, the examples in the book are implemented in IPython, so you can start using it right away and tweaking the code so you can learn it interactively.
Ces commentaires ont-ils été utiles ?   Dites-le-nous
Rechercher des commentaires

Discussions entre clients

Le forum concernant ce produit
Discussion Réponses Message le plus récent
Pas de discussions pour l'instant

Posez des questions, partagez votre opinion, gagnez en compréhension
Démarrer une nouvelle discussion
Thème:
Première publication:
Aller s'identifier
 

Rechercher parmi les discussions des clients
Rechercher dans toutes les discussions Amazon
   


Rechercher des articles similaires par rubrique