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Tuesday, October 16 • 2:30pm - 2:50pm
A Config-based Framework for Productionized Machine Learning

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For a data scientist, building correct models quickly and moving them to production safely can be challenging. Especially with messy data, catching and debugging data quality issues in model-building is also challenging. This talk will discuss the "Clover transform framework", a config-based production machine learning framework to allow easy and fast generation of features and models, for fast iteration speeds, easy parameter tuning, algorithm choice, monitoring, and auditability, using the same config for both development iteration and running in production.
Speakers
avatar for Melanie Goetz

Melanie Goetz

Head of Machine Learning, Clover Health
Melanie runs the Machine Learning team at Clover Health, a health insurance startup in San Francisco that uses machine learning to keep members healthy and out of the hospital. She studied Linguistics and Math/CS at MIT and ML at UPenn. Previously, she worked in Japan on machine translation... Read More →

Tuesday October 16, 2018 2:30pm - 2:50pm EDT
Deborah Sampson
  ML Engineering & ScienceOps

Attendees (36)