The hardest parts of data science

Defining feasible problems and coming up with reasonable ways of measuring solutions is harder than building accurate models or obtaining clean data.

November 23, 2015

Learning to rank for personalised search (Yandex Search Personalisation – Kaggle Competition Summary – Part 2)

My team’s solution to the Yandex Search Personalisation competition (finished 9th out of 194 teams).

February 11, 2015

Is thinking like a search engine possible? (Yandex search personalisation – Kaggle competition summary – part 1)

Insights on search personalisation and SEO from participating in a Kaggle competition (finished 9th out of 194 teams).

January 29, 2015

Fitting noise: Forecasting the sale price of bulldozers (Kaggle competition summary)

Summary of a Kaggle competition to forecast bulldozer sale price, where I finished 9th out of 476 teams.

November 19, 2014

What is data science?

Data science has been a hot term in the past few years. Still, there isn’t a single definition of the field. This post discusses my favourite definition.

October 23, 2014

Greek Media Monitoring Kaggle competition: My approach

Summary of my approach to the Greek Media Monitoring Kaggle competition, where I finished 6th out of 120 teams.

October 7, 2014

How to (almost) win Kaggle competitions

Summary of a talk I gave at the Data Science Sydney meetup with ten tips on almost-winning Kaggle competitions.

August 24, 2014

Kaggle competition tips and summaries

Pointers to all my Kaggle advice posts and competition summaries.

April 5, 2014

Kaggle beginner tips

First post! An email I sent to members of the Data Science Sydney Meetup with tips on how to get started with Kaggle competitions.

January 19, 2014