Kaggle is the world’s biggest predictive modelling competition platform and has half a million members. Companies such as Amazon, Facebook and Microsoft host data challenges such as:
- Predicting a topic or sentiment from text
- Predicting species from an image
- Predicting sales according to a store, product or area
- Predicting marketing response
As much as I would like to focus on the achievement, I can’t ignore the almost-three wonderful years it took to get there. I have learned a lot and had so much fun during the process. Believe it or not, I was originally inspired by horse racing.
At the University of Southampton, an entrepreneur talked to us about how he was able to predict horse races using regression analysis. I wanted to learn more. I learned statistical tools and became passionate, also picking up programming skills like Python, R and Java.
Over three years I entered over 100 competitions, participated with 50+ different teams, came in the top ten 25 times, was a prize winner 10 times. Ultimately I was ranked number one out of 480,000 data scientists.
So what did I learn? What wins competitions, in short is:
- Understanding the problem
- Try problem-specific things or new approaches
- The hours you put in
- The right tools
Another key element in wining competitions is to combine or ensemble various models.
The good thing is that many of the above processes can be automated. I am excited to be working on a product called Driverless ai which does just that – as well as winning multiple awards this year!
Marios is one of the key speakers at DataFest 2018, which kicks off today.