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How A Manager Became a Believer in DevOps for Machine Learning

Posted Mar 30, 2023 | Views 152
# DevOps
# Language Modeling
# Healthcare Technology
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SPEAKER
Keith Trnka
Keith Trnka
Keith Trnka
Currently on break, but previously Director of Data Science @ Currently on break, but previously 98point6

Keith has been in the industry for about 11 years. Most recently he was the Director of Data Science at 98point6 where we made telemedicine visits easier for doctors using natural language processing, machine learning, backend engineering, AWS, and frontend engineering. Prior to that, Keith improved the language models used in mobile phone keyboards at Swype and Nuance. And before that, He did his Ph.D. thesis in language modeling for assistive technology.

Currently, Keith is traveling, mentoring, and doing a side project on machine translation.

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Keith has been in the industry for about 11 years. Most recently he was the Director of Data Science at 98point6 where we made telemedicine visits easier for doctors using natural language processing, machine learning, backend engineering, AWS, and frontend engineering. Prior to that, Keith improved the language models used in mobile phone keyboards at Swype and Nuance. And before that, He did his Ph.D. thesis in language modeling for assistive technology.

Currently, Keith is traveling, mentoring, and doing a side project on machine translation.

+ Read More
SUMMARY

Keith Trnka, a seasoned leader in the technology industry, set foot on the MLOps Podcast in a special episode where he shared insights into his experience leading data teams and machine learning teams, becoming a better software engineer, and overseeing a successful migration from a monolith to microservices in the healthcare sector without any downtime.

Keith's background includes directing data science at 98.6, improving language models at swipe and nuance, and completing a Ph.D. thesis in language modeling for assistive technology. His work in these areas has contributed to the development of technology applications for healthcare, including telemedicine visits using natural language processing and machine learning.

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