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Mastering Clojure Data Analysis Paperback – May 26, 2014
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About the Author
Eric Rochester enjoys reading, writing, and spending time with his wife and kids. When he's not doing these things, he likes to work on programs in a variety of languages and platforms. Currently, he is exploring functional programming languages, including Clojure and Haskell. He has also written Clojure Data Analysis Cookbook, Packt Publishing. He works at the Scholars' Lab library at the University of Virginia, helping the professors and graduate students of humanities realize their digitally informed research agendas.
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Top customer reviews
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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)
Aside from one paragraph in the preface, the author doesn't spend a lot of time building a case for why one should use Clojure for data analysis, as opposed to R, MATLAB, Python, etc. It would have been nice to include a few example implementations in other languages in order to illustrate why Clojure makes the code more readable, maintainable, extensible, suitable for concurrent processing, etc. Likewise, although we are introduced to a number of libraries like D3.js, MALLET and Weka, the author doesn't go out of his way to justify his choices or even let the reader know what alternatives exist.
Overall, despite my reservations, I did find the book quite useful. I approached the subject already sold on the benefits of functional programming in a LISP-based language. Many of the examples introduced me to libraries or aspects of Clojure programming that I didn't previously know about.
When I learn a new language or technology I like to read three books at a time; two practical with plenty of examples to follow along with and one that I can read away from the computer (usually about theory or patterns).
Eric's excellent Clojure Data Analysis Cookbook [Packt] was one of two of the practical books I read when I was first beginning to work with the language. This book is in the same vein as the cookbook version, but more in-depth on data analysis. The necessary "how do I do this with Clojure" isn't absent nor does it take a back seat.
While I've only completed the first chapter I'd say this book is likely a great title for anyone who is an experienced software engineer coming to Clojure. Like the cookbook you'll learn how to write practical elegant Clojure code, not just theory, and a lot about data analysis and how to model data problems with Clojure.
The only gripe I have about this book is that the PDF version is inconsistent with its usage of color graphics and black and white graphics; the entire PDF version should present only color figures.
Having worked on sports statistics, analysing sport events, financial systems and now safety software, there is still a lot to learn and explore. Data analysis was part of all projects, but reading this book showed we only scratched the surface. Mastering Clojure Data Analysis certainly gave me new insights and ideas how to improve the software I am currently working on. The story telling format of the book is well suited for learning. The presented material tend to stick in my mind pretty easy.
This book provides applications of a number of well known tools, libraries and techniques, like Leiningen, Ring, D3.js, Reducers, Incanter and Compojure. Since the book uses many external clojure and java libraries, the examples won't run in the .NET implementation of Clojure.