Mastering Clojure Data Analysis

Mastering Clojure Data Analysis
Mastering Clojure Data Analysis is published by in May 2014. This book has 350 pages in English, ISBN-13 978-1783284139.

Clojure is a Lisp dialect built on top of the Java Virtual Machine. As data increasingly invades more and more parts of our lives, we continually need more tools to deal with it effectively. Data can be organized effectively using Clojure data tools.

Mastering Clojure Data Analysis teaches you how to analyze and visualize complex datasets. With this book, you’ll learn how to perform data analysis using established scientific methods with the modern, powerful Clojure programming language with the help of exciting examples drawn from real-world data. This will help you get to grips with advanced topics such as network analysis, the characteristics of social networks, applying topic modeling to get a handle on unstructured textual data, and GIS analysis to apply geospatial techniques to your data analysis problems.

With this guide, you’ll learn how to leverage the power and flexibility of Clojure to dig into your data and access the insights it hides.

What you will learn from this book

  • Use geospatial data to learn about geographical patterns in data
  • Use sentiment analysis to determine people’s opinions from online reviews
  • Frame and implement statistical experiments
  • Use A/B testing to determine the best
  • UI to keep users engaged
  • Work with time series data
  • Learn how to use parallelization and concurrency to work with large datasets
  • Use topic modeling to find the subjects discussed in a group of documents
  • Use network analysis to learn about online social networks


This book consists of a practical, example-oriented approach that aims to help you learn how to use Clojure for data analysis quickly and efficiently.

Who this book is written for

This book is great for those who have experience with Clojure and need to use it to perform data analysis. This book will also be hugely beneficial for readers with basic experience in data analysis and statistics.

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