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Today we're joined by Alex Ratner, Ph.D. student at Stanford, to discuss his work on Snorkel, a framework for creating training data with weak supervised learning techniques.
With Snorkel, Alex and his team hope to tackle the ever-present issue of having large data sets available by having users instead write a set of labeling functions, or scripts that programmatically label data. In our conversation, we discuss the original inspiration for Snorkel and some of the projects they've undertaken since it's inception. We also discuss some of the papers that have been presented at various conferences, that used Snorkel for training data, including Kunle Olokotun's "Software 2.0" presentation that we broke down in our 2018 NeurIPS series.
