Kaggle beginners

Last week, I gave a talk at the Data Science Sydney Meetup group about some of the lessons I learned through almost winning five Kaggle competitions. The core of the talk was ten tips, which I think are worth putting in a post (the original slides are here). Some of these tips were covered in my beginner tips post from a few months ago. Similar advice was also recently published on the Kaggle blog – it’s great to see that my tips are in line with the thoughts of other prolific kagglers....

These are few points from an email I sent to members of the Data Science Sydney Meetup. I suppose other Kaggle beginners may find it useful. My first steps when working on a new competition are: Read all the instructions carefully to understand the problem. One important thing to look at is what measure is being optimised. For example, minimising the mean absolute error (MAE) may require a different approach from minimising the mean square error (MSE)....