Ask Why! Finding motives, causes, and purpose in data science

Video and summary of a talk I gave at the Data Science Sydney meetup, about going beyond the what & how of predictive modelling.

September 19, 2016

Diving deeper into causality: Pearl, Kleinberg, Hill, and untested assumptions

Discussing the need for untested assumptions and temporality in causal inference. Mostly based on Samantha Kleinberg’s Causality, Probability, and Time.

May 14, 2016

Why you should stop worrying about deep learning and deepen your understanding of causality instead

Causality is often overlooked but is of much higher relevance to most data scientists than deep learning.

February 14, 2016

This holiday season, give me real insights

Some companies present raw data or information as “insights”. This post surveys some examples, and discusses how they can be turned into real insights.

December 8, 2015