A technical dive into model monitoring with open source experts Evidently AI CTO and Co-Founder Emeli Dral, looking at their product suite and approach to model monitoring with open source technology.
Followed by a look under the hood of Bumble's machine learning engineering ,with a focus on model monitoring - including their approach, paradigms and thoughts on best practice, with Gleb Vazhenin.
The evening will be compèred by Liam Wilson, Commercial Director & Matt Squire, CTO of fuzzy labs, open source MLOps specialists.
We'll have a Q&A chat box open throughout the event and will make it through as many as possible in the time.
Evidently is a first-of-its-kind monitoring tool that makes debugging machine learning models simple and interactive. It's really easy to get started!
This session will be led by Emeli Dral, CTO & Co-Founder of Evidently, who will offer us a technical insight into how Evidently works and the problems they can solve when it comes to monitoring machine learning models.
Emily is the CTO & Co-Founder of Evidently, a first-of-its-kind monitoring tool that makes debugging machine learning models simple and interactive.
In this session, Fuzzy Labs CTO & Co Founder Matt Squire briefly answers the question What is MLOps?
Matt has spent his career building high-scale, data-driven applications in many domains including advertising, price comparison, biometrics, and IoT. He's passionate about productionising machine learning through great open source tooling.
A technical deep dive into how Bumble approach model monitoring using open source tooling with Machine Learning Engineer Gleb Vazhenin.
Bumble is a household name in the world of online dating and have harnessed the power of data and machine learning to not only focus on better matches, but safety & integrity.
Gleb is an ML Engineer at Bumble.