Threading in Python is simple. It allows you to manage concurrent threads doing work at the same time. The library is called “threading”, you create “Thread” objects, and they run target functions for you. You can start potentially hundreds of threads that will operate in parallel. Speed up long running tasks by parallelising and threading computation where you can.
Python Flask web pages can be asynchronously updated by your Python Flask server at any point without user interaction. We’ll use Python Flask and the Flask-SocketIO plug-in to achieve this in this tutorial.
FAST TRACK: There is some python code that allows you to scrape bike availability from bike schemes at the bottom of this post… SLOW TRACK: As a recent aside, I was interested in collecting Dublin Bikes usage data over a long time period for data visualisation and exploration purposes. The Dublinbikes scheme was launched in …
Self-Organising Maps Self-Organising Maps (SOMs) are an unsupervised data visualisation technique that can be used to visualise high-dimensional data sets in lower (typically 2) dimensional representations. In this post, we examine the use of R to create a SOM for customer segmentation. The figures shown here used use the 2011 Irish Census information for the …
Self-Organising Maps for Customer Segmentation using R Read More »
“Is there any online reading or courses I can do to get into data analysis?” At my workplace, I get asked the question above. The question is usually posed by people typically with a finance background, who’s working as a management consultant. In this post I propose a learning path for such people to “get …
The Web Summit, Europes largest technology-industry conference was held in Dublin this week. An annual event since 2010, the Web Summit attracted over ten thousand visitors from over 90 countries. The Web Summit puts Ireland on the international startup and internet scene. With speakers like Elon Musk (founder of Paypal, SpaceX, and Tesla) and representatives from …