New insights at data4food challengePublished on: Author: Pim van de Pavoordt Category: Data Science
The Data4Food Challenge is just around the corner, which means three days of inspiration, fun and hard work. That weekend will be filled with challenges and I'm in full-on preparation mode for the hackathon that will focus on finding solutions for better global food distribution.
I plan to start preparing at home by learning all about the data sets that are available online. I've already done some much-needed research on the global food shortage. My colleagues and I plan to brainstorm about different ideas we can apply during the hackathon. Last but not least, I plan to turn in early the night before. I'm sure I'll need the extra energy for the hackathon!
It's going to be a weekend full of new insights. We're working in teams with participants from different disciplines. I'm sure other people will come up with ideas that I never would have thought of.
Challenge: one idea, lots of people
The biggest challenge during the hackathon will be coming up with one idea that the entire team can get behind. Working together with people from all walks of life is sure to bring new insights and opinions. A techie may look at a problem more pragmatically, while a policymaker may be concerned with the ethical side of things.
It's going to be interesting. I'm curious how other people view the food shortage and look forward to hearing their Big Data solutions. It's going to be a great learning experience. Although I have quite a bit of experience with data science, there are sure to be team members who know other techniques and approach problems and solutions from a totally different angle. I think the people with a non-technical take on things, like policymakers, will teach me a lot.
The Data4Food Challenge will also help me work on my own professional development. I'll be able to apply the techniques I learn from others in my work as a data scientist. I'll also learn more about how non-technical people view Big Data and discover new ways to explain what I do without becoming too technical. This could help me explain things more clearly to clients during projects.
In my daily work I also analyze huge volumes of data. We're currently busy categorizing 350 million tweets based on gender, using different techniques like Natural Language Processing, Support Vector Machines and Naive Bayes Classifiers. We also visualize the data. I think these experiences will come in handy during the hackathon.
I hope it will lead to lots of new ideas and prototypes that have the potential to reduce global hunger and deal with food sources more efficiently. I also hope these ideas and prototypes will be diverse enough to address other problems as well. I'm looking forward to it!