Speaker
Mr
Iain Keaney
(Skellig)
Description
Machine Learning (ML) has been proven to be a promising tool for researchers in many
fields and disciplines. However, the barrier to entry has been too high as the time it takes to
become proficient enough on ML frameworks can be quite long. Yet domain experts, rather
than machine learning engineers, always have the best insight into solving problems. Fast.ai
abstracts away much of the difficulty in building quality ML models, making it easier for
domain experts to apply it to their own work. Here we demonstrate how Fast.ai works. We talk about its accuracy/reliability and footprint in both memory and FLOPS when we repeated some research papers, getting superior results with only a few lines of code
