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:
- âĄď¸Charlene on LinkedIn â https://www.linkedin.com/in/charlenechambliss/
- âĄď¸Charlene on Twitter â https://twitter.com/blissfulchar
Recommendations:
- đŹ3blue1brown â Awesome YouTube channel about math & science: https://www.youtube.com/c/3blue1brown
- đNLP Highlights â Allen AI Insititute podcast about NLP research: https://soundcloud.com/nlp-highlights
- đSoftware engineering daily: https://softwareengineeringdaily.com/
- đTWiML â Another great podcast about machine learning and AI: https://twimlai.com/
- đ°Sebastian Ruder's blog and newsletter about NLP and ML: https://ruder.io/
- đ°Taming the Tail: Adventures in Improving AI Economics: https://a16z.com/2020/08/12/taming-the-tail-adventures-in-improving-ai-economics/
- đ°State of AI report (2021): https://www.stateof.ai/
- đLearn to learn â Ultralearning by Scott Young: https://www.scotthyoung.com/
đCheck Out Our Website! https://dagshub.com
Social Links:
- đŚLinkedIn: https://www.linkedin.com/company/dagshub
- đŚTwitter: https://twitter.com/TheRealDAGsHub
- đŚDean Pleban: https://twitter.com/DeanPlbn
