World Model · podcast knowledge graph

Deep Learning for NLP: From the Trenches with Charlene Chambliss - #433

2020-12-03 · 46 min · episode 433 · 14 entities

episode page audio

Asserted relationships

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    Deep Learning for NLP: From the Trenches with Charlene Chambliss - #433
  • → hosted by Sam Charrington person
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    Feed author/publisher: Sam Charrington
  • → discusses Science concept
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  • → discusses Technology company
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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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    evidence rules-v4
    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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    evidence rules-v4
    Feed category: Technology
  • hosted by TWIML company
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    evidence rules-v4
    Feed author/publisher: TWIML

persons 3

  • mentioned Charlene Chambliss person
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    Deep Learning for NLP: From the Trenches with Charlene Chambliss - #433
  • 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 Charlene Chambliss, Machine Learning Engineer at Primer AI.  Charlene, who we also had the pleasure of hosting at NLP Office Hours during TWIMLfest, is back to share some of the work she’s been doing with NLP. In our conversation, we explore her experiences working with newer NLP models and tools like BERT and HuggingFace, as well as whats she’s learned along the way with word embeddings, labeling tasks, debugging, and more. We also focus on a few of her projects, like her popular multi-lingual BERT project, and a COVID-19 classifier.  Finally, Charlene shares her experience getting into data science and machine learning coming from a non-technical background, and what the transition was like, and tips for people looking to make a similar shift.