Industrial Machine Learning and Building Tools for Data and Model Monitoring with Evidently AI Co-Founders Elena Samuylova and Emeli Dral

Machine Learning Engineered

Feb 16 2021 • 1 hr 21 mins

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://evidentlyai.com/ (https://evidentlyai.com/) https://twitter.com/elenasamuylova (https://twitter.com/elenasamuylova) https://twitter.com/EmeliDral (https://twitter.com/EmeliDral) 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 (http://cyou.ai/newsletter) Follow Charlie on Twitter: https://twitter.com/CharlieYouAI (https://twitter.com/CharlieYouAI) Subscribe to ML Engineered: https://mlengineered.com/listen (https://mlengineered.com/listen) Comments? Questions? Submit them here: http://bit.ly/mle-survey (http://bit.ly/mle-survey) Take the Giving What We Can Pledge: https://www.notion.so/charlieyou/Content-Pipeline-af923f8b990646369a85a00a348a1e12 (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: https://github.com/evidentlyai/evidently (Evidently on Github) https://evidentlyai.com/blog (Evidently AI's Blog) https://us.macmillan.com/books/9780374533557 (Thinking Fast and Slow) https://www.goodreads.com/book/show/66354.Flow (Flow) https://www.effectivealtruism.org/doing-good-better/ (Doing Good Better)