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Clojure Data Analysis Cookbook

More Information
Learn
  • Create beautiful, insightful graphs that you can publish to the Internet
  • Apply powerful clustering and data mining techniques to better understand your data
  • Use powerful data analysis libraries like Incanter, Hadoop, and Weka to get things done quickly
  • Interface with Mathematica and R to use the powerful analysis features they provide
  • Process data concurrently and in parallel for faster performance
  • Transform data to make it more useful and easier to analyze

 

About

Data is everywhere and it's increasingly important to be able to gain insights that we can act on. Using Clojure for data analysis and collection, this book will show you how to gain fresh insights and perspectives from your data with an essential collection of practical, structured recipes.

"The Clojure Data Analysis Cookbook" presents recipes for every stage of the data analysis process. Whether scraping data off a web page, performing data mining, or creating graphs for the web, this book has something for the task at hand.

You'll learn how to acquire data, clean it up, and transform it into useful graphs which can then be analyzed and published to the Internet. Coverage includes advanced topics like processing data concurrently, applying powerful statistical techniques like Bayesian modelling, and even data mining algorithms such as K-means clustering, neural networks, and association rules.

Features
  • Get a handle on the torrent of data the modern Internet has created
  • Recipes for every stage from collection to analysis
  • A practical approach to analyzing data to help you make informed decisions
Page Count 342
Course Length 10 hours 15 minutes
ISBN 9781782162643
Date Of Publication 25 Mar 2013

Authors

Eric Rochester

Eric Rochester enjoys reading, writing, and spending time with his wife and kids. When he’s not doing these things, he programs in a variety of languages and platforms, including websites and systems in Python, and libraries for linguistics and statistics in C#. Currently, he is exploring functional programming languages, including Clojure and Haskell. He works at Scholars’ Lab in the library at the University of Virginia, helping humanities professors and graduate students realize their digitally informed research agendas. He is also the author of Mastering Clojure Data Analysis, Packt Publishing.