Analyzing NYC Taxi dataset with Elasticsearch and Kibana(19th March 2017) |
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The NYC taxicab dataset has seen lots of love from many data scientists such as Todd W. Scheider and Mark Litwintschik. I decided to give it a go while learning Clojure, as I suspected that it might be a good language for ETL jobs. This article describes how I loaded the dataset, normalized its conventions and columns, converted from CSV to JSON and stored them to Elasticsearch.
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Mustache templates in Clojure(25th January 2017) |
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Mustache is a well-known template system with implementations in most popular languages. At its core it is logicless same templates can be directly used on other projects. For example I am planning to port this blgo engine from PHP to Clojure but I only need to replace LaTeX parsing and HTML generation parts, I should be able to use existing Mustache templates without any modifications. To learn Clojure programming I decided not to use the recommended library but instead implement my own.
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English hyphenation algorithm in Clojure(17th August 2016) |
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This is nothing that spectacular (as if anything on my blog is), but I still wanted to describe the outline of the project of porting the hyphenation algorithm from PHP to Clojure. The implementation is only about 80 lines of code + comments + 20 lines of unit tests. For comparison the original PHP abomination is about is about 160 LoCs, although it is a bit bloated by implementing the patterns search via a trie data structure instead of using the strpos function.
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Scalable analytics with Docker, Spark and Python(23rd December 2015) |
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Traditionally data scientists installed software packages directly to their machines, wrote code, trained models, saved results to local files and applied models to new data in batch processing style. New data-driven products require rapid development of new models, scalable training and easy integration to other aspects of the business. Here I am proposing one (perhaps already well-known) cloud-ready architecture to meet these requirements.
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