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Four Key Tools for Robust Enterprise NLP with Yunyao Li - #537
Manage episode 307469089 series 2355587
Today we’re joined by Yunyao Li, a senior research manager at IBM Research.
Yunyao is in a somewhat unique position at IBM, addressing the challenges of enterprise NLP in a traditional research environment, while also having customer engagement responsibilities. In our conversation with Yunyao, we explore the challenges associated with productizing NLP in the enterprise, and if she focuses on solving these problems independent of one another, or through a more unified approach.
We then ground the conversation with real-world examples of these enterprise challenges, including enabling level document discovery at scale using combinations of techniques like deep neural networks and supervised and/or unsupervised learning, and entity extraction and semantic parsing to identify text. Finally, we talk through data augmentation in the context of NLP, and how we enable the humans in-the-loop to generate high-quality data.
The complete show notes for this episode can be found at twimlai.com/go/537
700 tập
Four Key Tools for Robust Enterprise NLP with Yunyao Li - #537
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Manage episode 307469089 series 2355587
Today we’re joined by Yunyao Li, a senior research manager at IBM Research.
Yunyao is in a somewhat unique position at IBM, addressing the challenges of enterprise NLP in a traditional research environment, while also having customer engagement responsibilities. In our conversation with Yunyao, we explore the challenges associated with productizing NLP in the enterprise, and if she focuses on solving these problems independent of one another, or through a more unified approach.
We then ground the conversation with real-world examples of these enterprise challenges, including enabling level document discovery at scale using combinations of techniques like deep neural networks and supervised and/or unsupervised learning, and entity extraction and semantic parsing to identify text. Finally, we talk through data augmentation in the context of NLP, and how we enable the humans in-the-loop to generate high-quality data.
The complete show notes for this episode can be found at twimlai.com/go/537
700 tập
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