History of Kaggle Grandmaster Laura Fink

Kaggle Grandmaster Laura Fink is the Head of Data Science at Mircomata. For this physicist turned data scientist, hackathons are above all about having fun. “As long as there are teammates to collaborate with, I always love hackathons,” she said.

In an exclusive interview with Analytics India Magazine, the physicist turned data scientist talked about her Kaggle Grandmaster journey.

AIM: How did your fascination with algorithms come about?

Laura Fink: I was not interested in coding from the start, but more in the natural sciences and mathematics. As far back as I can remember, I wanted to understand the world and the differences and similarities between living and inanimate objects. For this reason, I studied physics.

For my master’s thesis, I optimized a program to remove background noise from fluorescent cell video data. This was my first contact with code and machine learning. And I loved it! For me, coding is a creative process like art. It’s real craftsmanship.

AIM: What were the initial challenges and how did you overcome them?

Laura Fink: Well, I had no prior knowledge of coding when I read the code from my teammate who wrote the program. I had no idea. It was like reading a book in a foreign language. So I bought a little book on coding in Java to solve this problem. After that, I jumped into the code and started implementing my ideas.

AIM: What excites you the most about coding?

Laura Fink: You create something that processes information and does something with it. It’s like an awesome machine that you can copy as much as you want and can easily be modified and shared within the community. I particularly like the idea of ​​open source.

I don’t have a particular ritual to start coding, but I enjoy it the most in a relaxing atmosphere.

AIM: What does your machine learning tool stack look like?

Laura Fink: Usually I start exploring data using matplotlib, pandas, NumPy and seaborn. Then it depends on the problem. For computer vision, I like both TensorFlow and PyTorch. Otherwise, I often use scikit-learn. I also love exploring other tools, and Kaggle is a great sandbox for trying out new packages and getting your hands dirty with new tools.

AIM: How are you preparing for your first hackathon?

Laura Fink: If you don’t have any prior coding experience, it might be a good idea to do a little tutorial first or read a book to get you started. This way you can better focus on implementing your ideas during the hackathon instead of struggling with the basics.

AIM: What’s the worst experience you’ve ever had as a coder?

Laura Fink: The hardest challenge for me when I was a beginner was understanding git. The worst experiences or moments that made me sweat were related to merging code with git.

AIM: What drew you to Kaggle? How has your journey been so far?

Laura Fink: One day, a colleague told me about Kaggle, and I was hooked right away. At that time, there were only contests and notebooks were only published to share ideas – not to get upvotes. It was like a game that I was always looking for. Since then, the platform has evolved a lot, and over the years I’ve recognized that Kaggle is good for having fun and improving my skills in data science and machine learning. To learn something new, it is important to fail and adapt. If you’re still in your comfort zone and there’s no one to challenge, you won’t improve much.

AIM: What was your first Kaggle competition like?

Laura Fink: I felt overconfident and thought it would be easy. But after making my first submissions, the truth hit me. College classes were good to start with, but I needed hands-on experience to improve. I like that it’s not easy to climb the leaderboard. But, on the other hand, it’s a lot of fun working on myself to become a better data scientist.

AIM: How did you feel when you became a Kaggle grandmaster?

Laura Fink: My Grandmaster level is tied to the notebook branch of Kaggle. I used notebooks to improve myself and learn new skills and tools at my own pace. By sharing my learning experiences with the community, I connected with other passionate Kagglers and was able to get rid of my fear of showing my ideas. With work and children, I often worked on my notebooks in the evening/night when I had free time. When I became a grandmaster, I felt very happy and sad. It’s the same feeling you get when defeating the final enemy in a video game. I’m very happy that there are still branches left that I can explore to collect more levels.

PURPOSE: Tips for Kaggle success.

Laura Fink: Focus on the fun and don’t get tempted by the public leaderboard!

Sean N. Ayres