Automated Data Science & Machine Learning: An Interview with the Auto-sklearn Team

KDnuggets recently ran an Automated Data Science and Machine Learning blog contest, which garnered numerous entries and lots of appreciation for the winning posts and a pair of honorable mentions. The winning post, titled Contest Winner: Winning the AutoML Challenge with Auto-sklearn, written by Matthias Feurer, Aaron Klein, and Frank Hutten, all of the University of Freiburg, provides an overview of Auto-sklearn, an open-source Python tool that automatically determines effective machine learning pipelines for classification and regression datasets. The project is built around the successful scikit-learn library and won the recent AutoML challenge. Given the popularity of the post, we asked the authors if they would be interested in answering a few followup questions on themselves, their project, and automated data science in general. What follows is the result of this conversation. What if we start by having you introduce the members of the team and provide a little information on each of your backgrounds?