MLOps Meetup #23 // Monitoring the ML Stack // Lina Weichbrodt episode artwork

EPISODE · Jul 11, 2020 · 55 MIN

MLOps Meetup #23 // Monitoring the ML Stack // Lina Weichbrodt

from MLOps.community · host Demetrios

Join the Community: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://go.mlops.community/YTJoinIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Get the newsletter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://go.mlops.community/YTNewsletter⁠⁠How To Monitor Machine Learning Stacks - Why Current Monitoring is Unable to Detect Serious Issues and What to Do About It with Lina Weichbrodt.  Monitoring usually focuses on the “four golden signals”: latency, errors, traffic, and saturation. Machine learning services can suffer from special types of problems that are hard to detect with these signals. The talk will introduce these problems with practical examples and suggest additional metrics that can be used to detect them. A case study demonstrates how these new metrics work for the recommendation stacks at Zalando, one of Europe’s largest fashion retailers.  Lina has 8+ years of industry experience in developing scalable machine learning models and bringing them into production. She currently works as the Machine Learning Lead Engineer in the data science group of the German online bank DKB. She previously worked at Zalando, one of Europe’s biggest online fashion retailers, where she developed real-time, deep learning personalization models for more than 32M users.   Join our Slack community: https://go.mlops.community/slackFollow us on Twitter: @mlopscommunity  Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Lina on LinkedIn: https://www.linkedin.com/in/lina-weichbrodt-344a066a/

Episode metadata supplied by the publisher feed · Published Jul 11, 2020

Embed this episode

Ready to play

MLOps Meetup #23 // Monitoring the ML Stack // Lina Weichbrodt

0:00 55:53

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

No similar podcasts found.

Frequently Asked Questions

How long is this episode of MLOps.community?

This episode is 55 minutes long.

When was this MLOps.community episode published?

This episode was published on July 11, 2020.

Can I download this MLOps.community episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!