In this episode, I'm speaking with Charlene Chambliss, Software Engineer at Aquarium. Charlene has vast experience getting NLP models to production. We dive into the intricacies of these models and how they differ from other ML subfields, the challenges in productionizing them, and how to get excited about data quality issues.
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Relevant Links:
- ➡️Charlene on LinkedIn – https://www.linkedin.com/in/charlenechambliss/
- ➡️Charlene on Twitter – https://twitter.com/blissfulchar
Recommendations:
- 🎬3blue1brown – Awesome YouTube channel about math & science: https://www.youtube.com/c/3blue1brown
- 🎙NLP Highlights – Allen AI Insititute podcast about NLP research: https://soundcloud.com/nlp-highlights
- 🎙Software engineering daily: https://softwareengineeringdaily.com/
- 🎙TWiML – Another great podcast about machine learning and AI: https://twimlai.com/
- 📰Sebastian Ruder's blog and newsletter about NLP and ML: https://ruder.io/
- 📰Taming the Tail: Adventures in Improving AI Economics: https://a16z.com/2020/08/12/taming-the-tail-adventures-in-improving-ai-economics/
- 📰State of AI report (2021): https://www.stateof.ai/
- 📕Learn to learn – Ultralearning by Scott Young: https://www.scotthyoung.com/
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- 🐦Twitter: https://twitter.com/TheRealDAGsHub
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