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Building a Unified NLP Framework at LinkedIn with Huiji Gao - #481

2021-05-06 · 35 min · episode 481 · 14 entities

episode page audio

Asserted relationships

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    Building a Unified NLP Framework at LinkedIn with Huiji Gao - #481
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    Feed author/publisher: Sam Charrington
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    Feed category: Tech News
  • → hosted by TWIML company
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    Feed author/publisher: TWIML

Entities found in this episode

concepts 6

  • mentioned Science concept
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    Feed category: Science
  • mentioned Tech News concept
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    Feed category: Tech News
  • discusses Science concept
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    Feed category: Science
  • discusses News concept
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    Feed category: News
  • discusses Tech News concept
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    Feed category: Tech News
  • mentioned NLP concept
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    NLP

companys 4

  • mentioned TWIML company
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    Feed author/publisher: TWIML
  • mentioned Technology company
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    Feed category: Technology
  • discusses Technology company
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    Feed category: Technology
  • hosted by TWIML company
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    Feed author/publisher: TWIML

persons 3

  • mentioned Huiji Gao person
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    Building a Unified NLP Framework at LinkedIn with Huiji Gao - #481
  • mentioned Sam Charrington person
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    evidence rules-v4
    Feed author/publisher: Sam Charrington
  • hosted by Sam Charrington person
    0.55
    evidence rules-v4
    Feed author/publisher: Sam Charrington

podcasts 1

Episode description as stored
Today we’re joined by Huiji Gao, a Senior Engineering Manager of Machine Learning and AI at LinkedIn.  In our conversation with Huiji, we dig into his interest in building NLP tools and systems, including a recent open-source project called DeText, a framework for generating models for ranking classification and language generation. We explore the motivation behind DeText, the landscape at LinkedIn before and after it was put into use broadly, and the various contexts it’s being used in at the company. We also discuss the relationship between BERT and DeText via LiBERT, a version of BERT that is trained and calibrated on LinkedIn data, the practical use of these tools from an engineering perspective, the approach they’ve taken to optimization, and much more! The complete show notes for this episode can be found at https://twimlai.com/go/481.