Machine Learning Tips from a World Class Practitioner: Phil Brierley

Last Updated on June 7, 2016

Phil Brierley won the Heritage Health Prize Kaggle machine learning competition. Phil was trained as a mechanical engineer and has a background in data mining with his company Tiberius Data Mining. He is heavily into R these days and keeps a blog at Another Data Mining Blog.

In October 2013 he presented to the Melbourne Users of R special interest group. The title of his talk was “Techniques to improve the accuracy of your Predictive Models” and you can watch it below:

This is a great presentation if you would like insight into how a highly pragmatic and effective machine learning practitioner approaches problem solving. I want to highlight three points I took away from this presentation.

Pragmatism

Phil opens the presentation with a comment that “the proof of the pudding is in the eating” – you can only indicate that something is successful after you have tried it out. Phil is not interested in the great theory, he want’s evidence that a model works by looking at it’s result.

He comments that most problems involve data that relates to
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