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Machine Learning Pipelines for R

May 8, 2017
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Machine Learning Pipelines for R

Building machine learning and statistical models often requires pre- and post-transformation of the input and/or response variables, prior to training (or fitting) the models. For example, a model may require training on the logarithm of the response and input variables. As a consequence, fitting and then generating predictions from these models requires repeated application of … Continue reading

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elasticsearchr – a Lightweight Elasticsearch Client for R

November 28, 2016
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elasticsearchr – a Lightweight Elasticsearch Client for R

elasticsearchr: a Lightweight Elasticsearch Client for R Elasticsearch is a distributed NoSQL document store search-engine and column-oriented database, whose fast (near real-time) reads and powerful aggregation engine make it an excellent choice as an ‘analytics database’ for R&D, production-use or … Continue reading →

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Asynchronous and Distributed Programming in R with the Future Package

November 2, 2016
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Asynchronous and Distributed Programming in R with the Future Package

Every now and again someone comes along and writes an R package that I consider to be a ‘game changer’ for the language and it’s application to Data Science. For example, I consider dplyr one such package as it has … Continue reading →

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An R Function for Generating Authenticated URLs to Private Web Sites Hosted on AWS S3

September 19, 2016
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An R Function for Generating Authenticated URLs to Private Web Sites Hosted on AWS S3

Quite often I want to share simple (static) web pages with other colleagues or clients. For example, I may have written a report using R Markdown and rendered it to HTML. AWS S3 can easily host such a simple web … Continue reading →

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Building a Data Science Platform for R&D, Part 3 – R, R Studio Server, SparkR & Sparklyr

August 22, 2016
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Building a Data Science Platform for R&D, Part 3 – R, R Studio Server, SparkR & Sparklyr

Part 1 and Part 2 of this series dealt with setting up AWS, loading data into S3, deploying a Spark cluster and using it to access our data. In this part we will deploy R and R Studio Server to … Continue reading →

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