The 21st century is often referred to as the age of “Big Data” due to the unprecedented increase in the volumes of data being generated. As most of this data comes without labels, making sense of it is a non-trivial task. To gain insight from unlabelled data, unsupervised machine learning algorithms have been developed and continue to be refined. These algorithms determine underlying relationships within the data by grouping data points into cluster families. The resulting clusters not only highlight associations within the data, but they are also critical for creating predictive models for new data.
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Where do OPIGlets come from?
Now you might think the answer to this question is OSOWs, but in fact they come from a wide variety of Undergraduate degrees!
How to be a Bayesian – ft. a completely ridiculous example
Most of the stats we are exposed to in our formative years as statisticians are viewed through a frequentist lens. Bayesian methods are often viewed with scepticism, perhaps due in part to a lack of understanding over how to specify our prior distribution and perhaps due to uncertainty as to what we should do with the posterior once we’ve got it.
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