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Monitoring and Evaluating Data Sets ft. Emeli Dral and Elena Samuylova - ML 049
About this Episode
Emeli Dral and Elena Samuylova joins the Adventure to discuss the tools they have built to monitor data quality to determine where data problems occur, what they mean, and how to fix them. Panel
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- Ben Wilson
- Francois Bertrand
- Elena Samuylova
- Emeli Dral
- Evidently AI
- When to Retrain an Machine Learning Model? Run these 5 checks to decide on the schedule
- GitHub | evidentlyai/evidently
- LinkedIn: Elena Samuylova
- Twitter: Elena Samuylova ( @elenasamuylova )
- LinkedIn: Emeli Dral
- Twitter: Emeli Dral ( @EmeliDral )
- Databricks
- GitHub | BenWilson2/ML-Engineering
- GitHub | databrickslabs/automl-toolkit
- LinkedIn: Benjamin Wilson
- Top End Devs Coaching: If you have questions about how to grow your skills or take your career to the next level, join us on our next weekly coaching call. It's completely free.
- Podcast Bootcamp: Launch an Amazing Sounding Podcast in just 4 WEEKS! Work with a 13 year podcasting veteran to get your podcast started off on the right foot!
Advertising Inquiries: https://redcircle.com/brands
Privacy & Opt-Out: https://redcircle.com/privacy
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Hosts & Guests
No transcript available for this episode.
