Automating Production Level Machine Learning Operations on AWS
Toronto Machine Learning Series (TMLS) via YouTube
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Discover how to bridge the gap between data scientists and ML operations in this comprehensive conference talk. Explore the unique challenges of ML Ops and learn how to implement a "model factory" architecture for effective machine learning operations on AWS. Gain insights into automating production-level ML workflows, including CI/CD for data science, model governance, and quality assessment. Understand the differences between ML Ops and traditional DevOps, and see how cloud services can be integrated to support multiple ML models in production and development simultaneously. Watch a demo of a model factory that showcases quick feedback for model development, framework-agnostic tooling for model packaging, and platform-agnostic continuous deployment strategies.
Syllabus
Mark McQuade and Tanya Vucetic - Automating Production Level Machine Learning Operations on AWS
Taught by
Toronto Machine Learning Series (TMLS)