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Submit ReviewElena Samuylova and Emeli Dral are the co-founders of Evidently AI, where they build open source tools to analyze and monitor machine learning models. Elena was previously the head of the startup ecosystem at Yandex, director of business development at their data factory and chief product officer at Mechanica AI. Emeli was previously a data scientist at Yandex, chief data scientist at the data factory and Mechanica AI in addition to teaching machine learning both online and at multiple universities.
Learn more about Elena, Emeli, and Evidently AI:
https://twitter.com/elenasamuylova
Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: http://cyou.ai/newsletter
Follow Charlie on Twitter: https://twitter.com/CharlieYouAI
Subscribe to ML Engineered: https://mlengineered.com/listen
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Timestamps:
02:15 How Emeli and Elena each got started in data science
07:10 Applying machine learning across a wide variety of industries at the Yandex Data Factory
14:55 Using ML for industrial process improvement
23:35 Challenges encountered in industrial ML and technical solutions
27:15 The huge opportunity for ML in manufacturing
34:35 How to ensure safety when using models in physical systems
37:40 Why they started working on tools for data and ML monitoring
42:50 Different kinds of data drift and how to address them
48:25 Common mistakes ML teams make in monitoring
55:25 Features of Evidently AI's library
57:35 Building open source software
01:02:25 Technical roadmap for Evidently
01:05:50 Monitoring complex data
01:08:50 Business roadmap for Evidently
01:11:35 Rapid fire questions
Links:
Elena Samuylova and Emeli Dral are the co-founders of Evidently AI, where they build open source tools to analyze and monitor machine learning models. Elena was previously the head of the startup ecosystem at Yandex, director of business development at their data factory and chief product officer at Mechanica AI. Emeli was previously a data scientist at Yandex, chief data scientist at the data factory and Mechanica AI in addition to teaching machine learning both online and at multiple universities.
Learn more about Elena, Emeli, and Evidently AI:
https://twitter.com/elenasamuylova
Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: http://cyou.ai/newsletter
Follow Charlie on Twitter: https://twitter.com/CharlieYouAI
Subscribe to ML Engineered: https://mlengineered.com/listen
Comments? Questions? Submit them here: http://bit.ly/mle-survey
Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/
Timestamps:
02:15 How Emeli and Elena each got started in data science
07:10 Applying machine learning across a wide variety of industries at the Yandex Data Factory
14:55 Using ML for industrial process improvement
23:35 Challenges encountered in industrial ML and technical solutions
27:15 The huge opportunity for ML in manufacturing
34:35 How to ensure safety when using models in physical systems
37:40 Why they started working on tools for data and ML monitoring
42:50 Different kinds of data drift and how to address them
48:25 Common mistakes ML teams make in monitoring
55:25 Features of Evidently AI's library
57:35 Building open source software
01:02:25 Technical roadmap for Evidently
01:05:50 Monitoring complex data
01:08:50 Business roadmap for Evidently
01:11:35 Rapid fire questions
Links:
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