Back in 2018, when I first learned about hackathons, I had never written a line of code in Python, let alone participated in coding events. While I was excited about solving data science problems, my lack of coding skills was a severe hindrance in achieving this feat.
However, I was extremely resilient and took every challenge that came my way as a learning opportunity. I began to understand code-structures; my domain knowledge proved to be an asset in building accurate models, and consequently, I was able to not only participate in data science hackathons, but also quickly accelerate up the leaderboard at these competitions.
What seemed impossible before became possible. Within 3 months, not only had I taught myself how to code in Python, but was also on the top 10% of the leaderboard at my first ever data-science hackathon.
And, as they say, investments compound over time, and investments in knowledge pay the best interests. I could now see the returns of my investment and was looking for more opportunities to practice these skills.
I got my chance last month when I, along with my super-smart teammates, Christopher Goodrich, Taylor Kooy, and Meghan Weber, won first place in the ‘Best Insight’ category at the Carolina Data Challenge. A 24 hour data-hackathon organized by the University of North Carolina, Chapel Hill, the event witnessed over 250 participants, multiple workshops, hands-on machine learning activities, and mentoring sessions from industry experts.
As part of our analysis, we built a time series model to analyze the effects of the trade wars on U.S. Sorghum exports and quantitatively determine how the tariffs and trade barriers have affected U.S. farmers since April 2018.
Now that I’ve become proficient in Python, I want to help fellow coders overcome the dreaded ‘coding-phobia.’ So, I’ve published a comprehensive tutorial on ‘Predicting Doctor’s Consultation Fee’ – a hackathon hosted on MachineHack.com .
For anyone who’s interested in getting started with hackathons and is waiting for that initial push, here are two tutorials in Python to begin your data-science hackathon journey.
Tutorial 1 – Doctor’s Fee Prediction Challenge
Tutorial 2 – Simple hacks to accelerate to the top of hackathon leaderboard
Columnist: Supreet Deshpande