The MU DSA program hosted a cutting-edge PyTorch container cyberinfrastructure to support the tutorial participants.

The tutorial taught participants three key skills that are critical to advancing research in computational intelligence:

1) use of PyTorch machine learning library;
2) deep learning models and transfer learning techniques; and
3) fuzzy machine learning model fusion.

The tutorial session was be broken into these three portions, each of which culminated in code examples that could be immediately migrated from the tutorial to the participants own research thrusts (theories and applications). The session will concluded with a case study demonstrating how the components have been tied together for scientific studies in remote sensing.

The tutorial is provided as open source at: https://github.com/scottgs/FuzzyFusion_DeepLearning_Tutorial

The PyTorch container image is available at: https://hub.docker.com/r/muiidsa/singleuser-pytorch-cpu/tags