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Charles Feduke May 28, 2014

(This review is for the electronic PDF version of the book; there are some graphs in the book that I understand are printed black and white, and the author makes a PDF of color graphs available for download to accompany the print version.)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.

Amazon Verified review

Rick Beerendonk Jul 07, 2014

I really enjoyed reading this book. It is pleasantly different than most how-to books I have on my bookshelf. The book combines a number of interesting topics in a very readable way. By no means it is an introduction to Clojure or ClojureScript. But both are used extensively and the programs are discussed with enough detail to understand the working of the code, so well suited for the intermediate developer.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.

David J. Brunell Nov 14, 2014

As others have mentioned, the material in this book is organized as a series of case studies and is not an exhaustive survey of either Clojure or data analysis. On the one hand, the case-study format makes it easy to follow along with with the author's examples. In doing so, a number of Clojure and data analysis techniques can be learned, some of which will hopefully be useful to you. On the other hand, I often found myself uninterested in the subject material of the examples, and this reduced my desire to work through those examples to the end. A more diligent reader might derive greater benefit.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.

Alfred Xiao Jul 02, 2014

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)

david clark Jun 19, 2014

First off my disclaimer I volunteered to review 'Mastering Clojure Data Analysis' - http://j.mp/McDla . I did not receive any compensation outside of an electronic copy of the book. I volunteered because of my interests in both Clojure and data analysis. The book is structured in a series of independent chapters modeled like use cases. He does a very good job of covering the problem space and why the algorithm makes sense to use. I would say that the orders of the words in the title would be more appropriately ‘mastering data analysis using clojure’ as clojure isn’t the focus nor should it be. Since the chapters are independent that technology stacks are slightly different – i.e. incanter vs d3js, weka vs mallet etc. There isn’t 100% overlap in those libraries but there is definitely overlap. Also since it made sense to use these libraries the clojure code is really just java interop over them which is the correct and pragmatic choice. That is why I would change the ordering of the title. Overall I would rate this book 3.5/5.

Mastering Clojure Data Analysis: If you'd like to apply your Clojure skills to performing data analysis, this is the book for you. The example based approach aids fast learning and covers basic to advanced topics. Get deeper into your data.

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