Leverage the power and fl exibility of Clojure through this practical guide to data analysisAbout This BookExplore the concept of data analysis using established scientific methods combined with the powerful Clojure languageMaster Naïve Bayesian Classification, Benford's Law, and much more in ClojureLearn with the help of examples drawn from exciting, real-world dataWho This Book Is ForThis 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.
What You Will LearnUse geospatial data to learn about geographical patterns in dataUse sentiment analysis to determine people's opinions from online reviewsFrame and implement statistical experimentsUse A/B testing to determine the best UI to keep users engagedWork with time series dataLearn how to use parallelization and concurrency to work with large datasetsUse topic modeling to find the subjects discussed in a group of documentsUse network analysis to learn about online social networksIn DetailClojure 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.
I am an experienced programmer in Java, with some experience in Clojure, and I am interested but not an expert in Data Analysis. I have Eric’s previous book - Clojure Data Analysis Cookbook. Although the names of that book and this book (Mastering Clojure Data Analysis) look similar, they cover different aspects. The former talks more about data analysis tools and libraries in Clojure, like Incanter, Cascalog.
Yet this book tries to examine case studies and go into more depth from the perspective of data analysis. It doesn’t focus on the technologies that the implementation uses, instead, it walks the reader through many common areas in data analysis, such as (social) network analysis and topic modeling, which in themselves are interesting topics regardless of whether you use Clojure or not to tackle the problem. Having said that, the author also covers important aspects of related libraries and tools well, including the MALLET machine learning library, d3 for data visualization.
I like this book as it demonstrates interesting case studies in the data analysis world, and how these problems can be solved using Clojure (backed by libraries/tools which may not be written in Clojure but in Java) in a concise and elegant way.
All in all, since the nature of this book is to talk about data analysis using Clojure, it is neither a book about Clojure programming nor a book on the algorithmic aspects of data analysis or how Bayesian works in detail..
(from j.mp/McDla you can find official sample chapters)