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Speaker "Ben Hamner" Details Back

 

Topic

Lessons learned from running hundreds of Kaggle competitions

Abstract

At Kaggle, we’ve run hundreds of machine learning competitions and seen over 80,000 data scientists make submissions. One thing is clear: winning competitions isn’t random. We’ve learned that certain tools and methodologies work consistently well on different types of problems. Many participants make common mistakes (such as overfitting) that should be actively avoided. Similarly, competition hosts have their own set of pitfalls (such as data leakage). In this talk, I’ll share what goes into a winning competition toolkit along with some war stories on what to avoid. Additionally, I’ll share what we’re seeing on the collaborative side of competitions. Our community is showing an increasing amount of collaboration in developing machine learning models and analytic solutions. I’ll showcase examples of this and discuss how these types of collaboration will improve how data science is learned and applied.

Profile

Ben Hamner is Kaggle’s co-founder and CTO. At Kaggle, he currently’s focused on creating tools that empower data scientists to frictionlessly collaborate on analytics and promote their results. He has worked with machine learning across many domains, including natural language processing, computer vision, web classification, and neuroscience. Prior to Kaggle, Ben applied machine learning to improve brain-computer interfaces as a Whitaker Fellow at the École Polytechnique Fédérale de Lausanne in Lausanne, Switzerland. He graduated with a BSE in Biomedical Engineering, Electrical Engineering, and Math from Duke University.