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Clojure for Data Science

Clojure for Data Science

By : Garner
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Clojure for Data Science

Clojure for Data Science

5 (4)
By: Garner

Overview of this book

The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist’s diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you’ll see how to make use of Clojure’s Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don’t yet exist. Even seasoned Clojure developers will develop a deeper appreciation for their language’s flexibility! You’ll learn how to apply statistical thinking to your own data and use Clojure to explore, analyze, and visualize it in a technically and statistically robust way. You can also use Incanter for local data processing and ClojureScript to present interactive visualisations and understand how distributed platforms such as Hadoop sand Spark’s MapReduce and GraphX’s BSP solve the challenges of data analysis at scale, and how to explain algorithms using those programming models. Above all, by following the explanations in this book, you’ll learn not just how to be effective using the current state-of-the-art methods in data science, but why such methods work so that you can continue to be productive as the field evolves into the future.
Table of Contents (12 chapters)
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11
Index

Running the examples

Each example is a function in the cljds.ch1.examples namespace that can be run in two ways—either from the REPL or on the command line with Leiningen. If you'd like to run the examples in the REPL, you can execute:

lein repl

on the command line. By default, the REPL will open in the examples namespace. Alternatively, to run a specific numbered example, you can execute:

lein run –-example 1.1

or pass the single-letter equivalent:

lein run –e 1.1

We only assume basic command-line familiarity throughout this book. The ability to run Leiningen and shell scripts is all that's required.

Tip

If you become stuck at any point, refer to the book's wiki at http://wiki.clojuredatascience.com. The wiki will provide troubleshooting tips for known issues, including advice for running examples on a variety of platforms.

In fact, shell scripts are only used for fetching data from remote locations automatically. The book's wiki will also provide alternative instructions for those not wishing or unable to execute the shell scripts.

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