Mining London cycle hire data in R using PhantomJS

This tutorial introduces a quick and efficient method to access large file dumps from JavaScript driven webpages in R. I developed the script to download the extensive cycle hire dataset from TfL's open data portal, however the code can easily be adapted to fit any web-based file dump.

Setting up large scale OSM environments for R using Osmosis and PostgreSQL with PostGIS

Integrating large datasets in R can sometimes be very tricky, especially when it comes to geographical data. As a convenient solution, here comes my tutorial on setting up a database environment for OSM data in PostgreSQL and how to access this data in R. You can either access it on my website (click 'read more') or via the R blog r-spatial.

Digital decentralization: lingering revolution

While all over the world, people marvel at self-driving cars and 3D-printers, a less glamorous yet much more far-reaching change emerges in the background of digitalization. Technological innovation will fundamentally convert our understanding of institutions.

Introduction to Machine Learning in R

This tutorial is the transcript of a Machine Learning workshop I hosted as a part of the Imperial College Data Science Society (ICDSS) talent development programme. The event aimed at conveying a basic understanding of Machine Learning (K-means Clustering, ANNs and SVMs) using comprehensive case studies. This document targets Machine Learning beginners and requires some elementary experience with R.

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