Below are slides from a talk given to the Bristol Clojurians on April 21st 2015.

The talk was in two parts, each around an hour, and in each I attempted to give a practical overview of several key techniques presented in Clojure for Data Science, including linear & logistic regression and k-means clustering. I also gave a brief demonstration of visualization with Quil and of writing a Hadoop job with Parkour to make use of the Mahout machine learning library.

The content of the slides is available at https://github.com/henrygarner/clojure-data-science. x

Tags: quil clojure data science k-means visualization statistics linear regression clustering correlation talks parkour logistic regression bayes theorem classification

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