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Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
 
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Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management [Versión Kindle]

Gordon S. Linoff , Michael J. Berry

Precio lista ed. digital: EUR 41,20 ¿Qué es esto?
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Descripción del producto

Descripción del producto

The leading introductory book on data mining, fully updated and revised!

When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition—more than 50% new and revised— is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company. 

  • Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems
  • Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately
  • Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more
  • Provides best practices for performing data mining using simple tools such as Excel

Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.


Detalles del producto

  • Formato: Versión Kindle
  • Tamaño del archivo: 14091 KB
  • Longitud de impresión: 891
  • Números de página - ISBN de origen: 0470650931
  • Editor: *Wiley Computer Publishing; Edición: 3 (23 de marzo de 2011)
  • Vendido por: Amazon Media EU S.à r.l.
  • Idioma: Inglés
  • ASIN: B004UB2KE4
  • Texto a voz: Activado
  • X-Ray: No activado
  • Clasificación en los más vendidos de Amazon: n°70.262 Pagados in Tienda Kindle (Ver el Top 100 de pago en Tienda Kindle)

Opiniones de clientes

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Amazon.com: 3.7 de un máximo de 5 estrellas  37 opiniones
30 de 31 personas piensan que la opinión es útil
5.0 de un máximo de 5 estrellas The first book on Data Mining everyone should read 4 de mayo de 1999
Por Gustavo Denicolay - Publicado en Amazon.com
Formato:Tapa blanda
It covers almost every aspect of data mining. It is clear, precise, goes to the point, and sometimes goes into some depth. If you are a marketing person, it will give you a very refined idea of what can be done with data mining, and what does it involves for your company ( remember the first thing you need is DATA!!). If you are an academic person, you will get a general idea of the different kinds of data analysis. You won't see any formulae or algorithms, after reading this book look for details somewhere else.
30 de 32 personas piensan que la opinión es útil
3.0 de un máximo de 5 estrellas Depends what you want this book for 1 de abril de 2001
Por Alex - Publicado en Amazon.com
Formato:Tapa blanda
This book gives an overview of what data mining is and the tools available to perform it; Market Basket Analysis, Memory Based Reasoning, Automatic Cluster Detection, Link Analysis, Decision Trees, Artificial Neural Networks. Genetic Algorithms are also included, which, while not a data mining tool, are being used to train neural nets.

In each case the authors describe the principles behind the tool, its strengths and weaknesses and applications were it is applicable. The authors give tips on what data preparation is required for the tool, both in terms of data "massaging", (which is required for neural nets) and indicate were it is important to select training sets that have approximately equal proportions of "good" & "bad" outcomes, in order for the tool to predict correctly.

The descriptions include simple examples of the tool to give an overview of how the tool works. But as the title indicates, this book is for users who are considering using data mining tools. It does not describe how to use particular applications, neither does it include code examples (pseudo or actual) if you are interesting in developing your own tools.

The book is easy to read and includes many examples from their experience of data mining in the real world.

19 de 20 personas piensan que la opinión es útil
4.0 de un máximo de 5 estrellas Good Introduction book, not limited to Marketing 9 de diciembre de 1997
Por crozas@adv.es - Publicado en Amazon.com
Formato:Tapa blanda
The authors explain in a detailed way the most popular Data Mining techniques. The topics about Neuronal Networks, Decision Trees, Market-Basket Analysis and Memory-Based Reasoning are excellent. I think the topic Genetic Algorithms could be a bit more developed, but for the beginner is a good first overview. I have missed a topic about fuzzy logic. Given that the 90% of Data Mining projects are based on Marketing (1:1), the book is absolutely suitable for starting with these concepts, although I feel the book can be used in any other field (Just-In-Time Inventory, Demand Forecasting, Supply Value Chain, etc.)

In my opinion, it was very useful for my work and I considered it as a reference book.
Ir a Amazon.com para ver las 37 opiniones existentes 3.7 de un máximo de 5 estrellas

Subrayados populares

 (¿Qué es esto?)
&quote;
Merely finding patterns is not enough. You must respond to the patterns and act on them, ultimately turning data into information, information into action, and action into value. &quote;
Subrayado por 23 usuarios de Kindle
&quote;
Data mining is a business process for exploring large amounts of data to discover meaningful patterns and rules. &quote;
Subrayado por 22 usuarios de Kindle
&quote;
The goal should be reaching prospects who are more likely to make purchases because of having been contacted. &quote;
Subrayado por 17 usuarios de Kindle

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