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.
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