Multi-modal Deep Learning for Complex Document Understanding with Doug Burdick - #541

Multi-modal Deep Learning for Complex Document Understanding with Doug Burdick - #541

Today we’re joined by Doug Burdick, a principal research staff member at IBM Research. In a recent interview, Doug’s colleague Yunyao Li joined us to talk through some of the broader enterprise NLP problems she’s working on. One of those problems is making documents machine consumable, especially with the traditionally archival file type, the PDF. That’s where Doug and his team come in. In our conversation, we discuss the multimodal approach they’ve taken to identify, interpret, contextualize and extract things like tables from a document, the challenges they’ve faced when dealing with the tables and how they evaluate the performance of models on tables. We also explore how he’s handled generalizing across different formats, how fine-tuning has to be in order to be effective, the problems that appear on the NLP side of things, and how deep learning models are being leveraged within the group. The complete show notes for this episode can be found at twimlai.com/go/541

Episoder(779)

Fighting Fraud with Machine Learning at Shopify with Solmaz Shahalizadeh - TWiML Talk #60

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25 Okt 201741min

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AI-Powered Conversational Interfaces with Paul Tepper - TWiML Talk #52

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6 Okt 201736min

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The show you’re about to hear is part of a series of shows recorded in San Francisco at the Artificial Intelligence Conference. This time around, I speak with Mo Patel, practice director of AI & deep ...

6 Okt 201745min

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