Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner

Overview

Data Mining has become an essential tool for any enterprise as vast amounts of data are gathered leading to what is now being popularly called "Big Data". Data is also termed as the new oil, and companies which know how to process/refine and harness this data are the ones which will thrive. Data Science or data mining is the art and science of finding useful patterns in the data and making it actionable. These patterns generate new insights and allow us to convert future ...

See more details below
Sending request ...

More About This Book

Overview

Data Mining has become an essential tool for any enterprise as vast amounts of data are gathered leading to what is now being popularly called "Big Data". Data is also termed as the new oil, and companies which know how to process/refine and harness this data are the ones which will thrive. Data Science or data mining is the art and science of finding useful patterns in the data and making it actionable. These patterns generate new insights and allow us to convert future uncertainties into actionable probabilities.

Whether you are brand new to data mining or working on your tenth predictive analytics project, Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner will show you how to analyze data and uncover hidden patterns and relationships to aid important decisions. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Vijay Kotu and Bala Deshpande show you the keys to mastering predictive analysis. You’ll be able to:

  • Get a comprehensive understanding of different data mining techniques, be prepared to select the right technique for a given data problem and be ready to create a general purpose analytics process.
  • Use RapidMiner, an open source, GUI based data mining tool to create and develop your own data mining processes without having to write complicated lines of programming code.
  • Get up and running fast with 20 commonly used powerful techniques for predictive analysis
  • Implement a simple 5 step process for implementing algorithms that can be used for performing predictive analytics.
  • Demystifies data mining concepts with easy to understand language
  • Shows how to get up and running fast with 20 commonly used powerful techniques for predictive analysis
  • Explains the process of using open source RapidMiner tools
  • Discusses a simple 5 step process for implementing algorithms that can be used for performing predictive analytics
  • Includes practical use cases and examples
Read More Show Less

Product Details

  • ISBN-13: 9780128014608
  • Publisher: Elsevier Science
  • Publication date: 12/12/2014
  • Pages: 352

Meet the Author

Vijay Kotu is Senior Director of Analytics at Yahoo. He leads analytics effort by implementation of large scale data systems and He supports operations of global sales, marketing, finance, and products by assembling and analyzing vast data gathered from company’s online operations. He has worked in the domain of business intelligence, data mining, web analytics, information design, and marketing analytics for more than ten years. He is a member of Association of Computing Machinery and is certified Six Sigma Black Belt from American Society of Quality.

Bala Deshpande is the founder of SimaFore, a custom analytics app development and consulting company. He has more than 20 years of experience in using analytical techniques in a wide range of application areas. His first exposure to predictive models and analytics was in the field of biomechanics - in identifying correlations and building multiple regression. He began his career as an engineering consultant following which he spent several years analyzing data from automobile crash tests and helping to build safer cars at Ford Motor Company. He has been instrumental in promoting information theory based analytical techniques for a range of applications from performance measurement in organizations to predicting patient stability in ICUs. He holds a PhD in Bioengineering from Carnegie Mellon and an MBA from Ross School of Business (Michigan).

Read More Show Less

Table of Contents

  1. Introduction
  2. Data Mining Process
  3. Data Exploration
  4. Classification
  5. Regression
  6. Association
  7. Clustering
  8. Model Evaluation
  9. Text Mining
  10. Time Series
  11. Anomaly Detection
  12. Advanced Data Mining
  13. Getting Started with RapidMiner
Read More Show Less
If you find inappropriate content, please report it to Barnes & Noble
Why is this product inappropriate?
Comments (optional)