In a previous post we wrote an article about an RShiny app for exploring traffic accidents in Scotland. Unfortunately, if we wanted to run this application today, we would face compatibility issues. Imagine, if as an organisation we decided to deploy this application somewhere else or a colleague, client or any user wanted to run […]
Data Storytelling
I’ve been thinking a lot about story lately – it’s such a key point about really engaging people with your work. Storytelling with facts, helping people to really understand a situation, is one way to describe a key data science skill. As part of this I’ve been looking into aspects of the storytelling craft, such […]
A Brief Profiling of Data Professions
Do you recall how many times you’ve read articles titled “This is what a Data Scientist does” or “Differences between a Data Scientist and a Data Analyst”? Such articles usually come with various colourful (and sometimes funnily shaped) Venn diagrams, arbitrarily presenting the overlap of the various data professions and highlighting the distribution of different […]
Synthetic data in machine learning
Machine learning algorithms are currently applied in multiple scenarios in which unbalanced datasets or overall lack of sufficient training data lead to their suboptimal performance. For example, approaches focusing on disease prediction are often affected because data in the health sector is generally difficult to acquire and disease training examples are limited. Fraud detection in […]
Using Generalised Additive Mixed Models (GAMMs) to Predict Visitors to Edinburgh and Craigmillar Castles
I’d been curious about generalised additive (mixed) models for some time, and the opportunity to learn more about them finally presented itself when a new project came my way, as part of my work at The Data Lab. The aim of this project was to understand the pattern of visitors recorded at two historic sites […]