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b'In this episode, I\\u2019m joined by David Rosenberg, data scientist in the office of the CTO at financial publisher Bloomberg, to discuss his work on \\u201cExtracting Data from Tables and Charts in Natural Document Formats.\\u201d Bloomberg is dealing with tons of financial and company data in pdfs and other unstructured document formats on a daily basis. To make meaning from this information more efficiently, David and his team have implemented a deep learning pipeline for extracting data from the documents. In our conversation, we dig into the information extraction process, including how it was built, how they sourced their training data, why they used LaTeX as an intermediate representation and how and why they optimize on pixel-perfect accuracy. There\\u2019s a lot of interesting info in this show and I think you\\u2019re going to enjoy it. The notes for this show can be found at twimlai.com/talk/126.'