undrgrnd Cliquez ici Baby Litte nav-sa-clothing-shoes nav-sa-clothing-shoes Cloud Drive Photos cliquez_ici Soldes Cliquez ici Acheter Fire Acheter Kindle Paperwhite cliquez_ici Jeux Vidéo Montres soldes Bijoux Soldes

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
 

Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R [Format Kindle]

Thomas Miller

Prix conseillé : EUR 37,97 De quoi s'agit-il ?
Prix livre imprimé : EUR 77,15
Prix Kindle : EUR 26,58 TTC & envoi gratuit via réseau sans fil par Amazon Whispernet
Économisez : EUR 50,57 (66%)

  • Longueur : 348 pages
  • Langue : Anglais
  • En raison de la taille importante du fichier, ce livre peut prendre plus de temps à télécharger
  • 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.
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 26,58  
Relié EUR 69,27  
-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

Today, successful firms compete and win based on analytics. Modeling Techniques in Predictive Analytics brings together all the concepts, techniques, and R code you need to excel in any role involving analytics. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains why the problem matters, what data is relevant, how to explore your data once you’ve identified it, and then how to successfully model that data. You’ll learn how to model data conceptually, with words and figures; and then how to model it with realistic R programs that deliver actionable insights and knowledge. Miller walks you through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. All example code is presented in R, today’s #1 system for applied statistics, statistical research, and predictive modeling; code is set apart from other text so it’s easy to find for those who want it (and easy to skip for those who don’t).

Quatrième de couverture

This uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you're new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you're already a modeler, programmer, or manager, it will help you master crucial skills you don't yet have.

 

Unlike most books on predictive analytics, this guide illuminates the discipline through practical case studies, realistic vignettes, and intuitive data visualizations–not complex mathematics. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through every step: defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more.

 

Each chapter focuses on one of today’s most important applications for predictive analytics, giving you the skills and knowledge to put models to work–and gain maximum value from them.


Détails sur le produit

  • Format : Format Kindle
  • Taille du fichier : 64452 KB
  • Nombre de pages de l'édition imprimée : 348 pages
  • Utilisation simultanée de l'appareil : Jusqu'à 5 appareils simultanés, selon les limites de l'éditeur
  • Editeur : Pearson FT Press; Édition : 1 (23 août 2013)
  • Vendu par : Amazon Media EU S.à r.l.
  • Langue : Anglais
  • ASIN: B00EQ8D30Q
  • Synthèse vocale : Activée
  • X-Ray :
  • Word Wise: Non activé
  • Composition améliorée: Activé
  • Classement des meilleures ventes d'Amazon: n°221.005 dans la Boutique Kindle (Voir le Top 100 dans la Boutique Kindle)

En savoir plus sur l'auteur

Découvrez des livres, informez-vous sur les écrivains, lisez des blogs d'auteurs et bien plus encore.

Commentaires en ligne

Il n'y a pas encore de commentaires clients sur Amazon.fr
5 étoiles
4 étoiles
3 étoiles
2 étoiles
1 étoiles
Commentaires client les plus utiles sur Amazon.com (beta)
Amazon.com: 3.9 étoiles sur 5  17 commentaires
54 internautes sur 57 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 More like a collection of magazine/newspaper articles than a book 27 décembre 2013
Par Prof Ed U. Cate - Publié sur Amazon.com
Format:Relié|Achat vérifié
I purchased this book before I had a chance to read any sample chapter and was disappointed after I went through the book.

Every chapter is dedicated to an application of a particular model of predictive analytics, where a (more or less) real problem is described and discussed, name of a model to use is mentioned, chart outputs are shown and used for a conclusion. In very much the same format and content of an article that you would see in for example Bloomberg business magazine. There is no substantial discussion of any of the models, and without a good understanding of such models you cannot conduct predictive Analytics.

The content of this book could be used in the first 2-3 weeks of an introductory course in Analytics discussing what is Analytics and what are some example applications. I ended up keeping the book mostly due to hassle of a return, and partly for using it as a list of major models to read elsewhere and learn.
19 internautes sur 19 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Good book for end-users 27 décembre 2013
Par JoeT - Publié sur Amazon.com
Format:Relié|Achat vérifié
This is a good book on using R for predictive modeling.
The books website contains all the code that is used in the book.
I tried all of the downloadable R files and they all worked as advertised.
I admit not trying the text processing though (Chapter 7) only because I don't like R for text processing.
Rather use perl or Rapidminer.

Pros:
1. All the code works
2. A good sample space of topics, so you get a feel of predictive modeling in different situations.
3. You really don't need an extensive math background, since there is virtually no math described at all.

Cons:
1. If there was one thing I wish was better done is the analysis of the results. Some of the results, unless you are already familiar with the statistical technique used, might seem foreign and will require you to do some additional research.

Summary:
Overall a good book, minus the 1-Con above.
Hint: If you do download the R programs, go through each one a piece at a time, to see what's going on. I found it's better than just "running the code". You'll have a better understanding of what's going on.
10 internautes sur 11 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Data/Code is available 1 octobre 2014
Par Shawn Mehan - Publié sur Amazon.com
Format:Relié
Why people are whinging that they can't find the downloadable programs and data sets is beyond me. http://www.ftpress.com/promotions/modeling-techniques-in-predictive-analytics-139480
10 internautes sur 13 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Best book on predictive analytical with a business perspective 18 septembre 2013
Par S. Wang - Publié sur Amazon.com
Format:Relié|Achat vérifié
So far the best book I have read on predictive analytics with a business perspective. ( I at least skim through almost all books on this topic) The first chapter is concise but clearly deciphered relationship among different modeling and PA techniques. Each of the other 11 chapters uses one business problem to illustrate one PA technique. The examples are all very well selected ---- I would say this is the primary reason I love the book ---- they are from real world, have direct impact on business decisions, use moderate-sized data set. The results are presented in meaningful visualizations ---- not overly complicated graphs as other books may do, yet creative enough to clearly show the business insights. One such example is figure 4.5.

The biggest drawback is I can not find the source code used in the book. To type them in is daunting. Hope the author would post them somewhere soon.
3 internautes sur 3 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Great Intro to Predictive Analytics 4 février 2014
Par Calvin - Publié sur Amazon.com
Format:Relié|Achat vérifié
I've read a few books now and been taking classes on data science but I've had trouble linking theory and the practice. This book has been a huge help in seeding ideas, and giving practical examples on how to execute those ideas. I appreciate the lack of downloadable source code as it has forced me to write the source by hand. Great book.
Ces commentaires ont-ils été utiles ?   Dites-le-nous

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