The application of machine learning (ML) and high performance computing (HPC) to humanities research
holds tremendous potential, but there are significant challenges to developing a community of experts that
can work together at this intersection of topic and technique. HPC experts may not have the background
necessary to appreciate how their tools can best be brought to bear on the diverse datasets and conceptual
approaches of humanities researchers, and humanities researchers may not have the well-honed
background in computational and statistical modeling that resides with ML or HPC specialists. We will
approach this topic by focusing on a few case studies in the humanities that illustrate how ML and HPC can
both be used to powerful effect, whether by streamlining the initial processing of massive data, modeling
and visualizing humanities-relevant datasets, or using deep learning frameworks and the speed and power of
GPUs to rapidly prototype predictive models.