DataScience SG Meetup - How we got top 3% in Kaggle
Eugene Yan
A data scientist shared their approach to achieving top 3% placement (85th out of 3514) in Kaggle's Otto competition at a Singapore meetup. The presentation covered specific techniques including feature engineering, transformation methods, machine learning models like trees and neural networks, and ensembling approaches. The talk provided a framework for competing in Kaggle competitions based on their practical experience.
Why it matters
Sharing about my first data science competition at DataScience SG.
