Sharing my Machine Learning hackathon participation experience. Hackathons are the best way to practice and get hands on experience. They bring out the best in us everytime, no exceptions. Look for hackathons that work for you, it’s better to work along the people rather than solving in silos (for learning at least)
Hackathons magically raise the enthusiasm and excitement of solving a problem. It takes the game altogether to a different level. Last week I solved my first machine learning problem for an online hackathon. I think hackathons bring the best out of us.
HackerEarth hosted a Machine Learning Challenge where the challenge was to predict the probability of a loan being defaulted based on a dataset of over 5L records with 45 attributes/columns.
Though I do solve some machine learning problems now and then, I was still mostly in a learning mode. But not anymore, this was the first decent and moderately difficult problem I solved. The learnings have been immense. I solved the challenge in Python achieving 97.6% accuracy. It’s posted on GitHub. I got a sense of what it takes to improve the accuracy point by point pushing the limits and getting the most insights out of data. And it all happens in hackathons when there is a leaderboard to compare the numbers, no matter where you stand on the leaderboard. It’s encouraging to see the accuracy figures in comparision ranked with other solutions as compared to solving the problem in silos. One might get content with 95% accuracy, but when we see it’s possible to do more with the same dataset, we push the limits of what we think we can do. Througout the 10 day Hackathon I gravitated on the leaderboard starting with 8th in the beginning rose to 4th at one point of time and then finally finished at 19th.