The workshop “Data Mining 4 Industrial Ecology” sponsored by the SUS section was a grand success at ISIE 2017 in Chicago. The workshop was the first one to fill up with about 45 participants.
The workshop was organized by Sybil Derrible (U. Illinois at Chicago) and Ming Xu (U. Michigan). The main goal of the workshop was to expose the industrial ecology community to machine learning (both supervised and unsupervised learning) and to focus specifically on three techniques: K-means clustering, Decision Tree Learning, and Neural Networks. No coding experience was required but the participants were taught rudimentary coding in Python and they used the free Python library Scikit-Learn.
The workshop received tremendous feedback, and the organizers hope to repeat it in the future. For more information about the workshop, please contact the lead organizer, Sybil Derrible (firstname.lastname@example.org).