Democratizing and automating machine learning

Ministrante: Dr. Joaquin Vanschoren, Eindhoven University of Technology, Netherlands


Building machine learning systems remains something of a (black) art, requiring a lot of prior experience to select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To democratize machine learning, and make it easily accessible to those who need it, we need a more principled approach to experimentation to understand how to build machine learning systems and progressively automate this process as much as possible. First, we created OpenML, an open science platform allowing scientists to share datasets and train many machine learning models from many software tools in a frictionless yet principled way. It also organizes all results online, providing detailed insight into the performance of machine learning techniques, and allowing a more scientific, data-driven approach to building new machine learning systems. Second, we use this knowledge to create automatic machine learning (AutoML) techniques that learn from these experiments to help people build better models, faster, or automate the process entirely.

CV resumido: ​ Joaquin Vanschoren is assistant professor of machine learning at the Eindhoven University of Technology (TU/e). His research focuses on the progressive automation of machine learning. He founded and leads, an open science platform for machine learning research used all over the world. He obtained several demonstration and application awards, the Dutch Data Prize, and has been invited speaker at ECDA, StatComp, AutoML@ICML, CiML@NIPS, Reproducibility@ICML, DEEM@SIGMOD and many other conferences. He also co-organized machine learning conferences (e.g. ECMLPKDD 2013, LION 2016) and many workshops, including the AutoML Workshop series at ICML.