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:
- ā”ļøCharlene on LinkedIn ā https://www.linkedin.com/in/charlenechambliss/
- ā”ļøCharlene on Twitter ā https://twitter.com/blissfulchar
Recommendations:
- š¬3blue1brown ā Awesome YouTube channel about math & science: https://www.youtube.com/c/3blue1brown
- šNLP Highlights ā Allen AI Insititute podcast about NLP research: https://soundcloud.com/nlp-highlights
- šSoftware engineering daily: https://softwareengineeringdaily.com/
- šTWiML ā Another great podcast about machine learning and AI: https://twimlai.com/
- š°Sebastian Ruder's blog and newsletter about NLP and ML: https://ruder.io/
- š°Taming the Tail: Adventures in Improving AI Economics: https://a16z.com/2020/08/12/taming-the-tail-adventures-in-improving-ai-economics/
- š°State of AI report (2021): https://www.stateof.ai/
- šLearn to learn ā Ultralearning by Scott Young: https://www.scotthyoung.com/
šCheck Out Our Website! https://dagshub.com
Social Links:
- š¦LinkedIn: https://www.linkedin.com/company/dagshub
- š¦Twitter: https://twitter.com/TheRealDAGsHub
- š¦Dean Pleban: https://twitter.com/DeanPlbn