[webMeetup] Debugging Machine Learning in Production

Join the 43rd NLP Zurich tech shindig online! Shreya Shankar (Machine Learning Engineer) will talk about modern ML infrastructures, when to promote models to production and case studies of "bugs" found by users. Tune in 2nd February to learn more.

We are looking forward to welcoming you!

Agenda:

17:55 Join the webinar
18:00 Shreya Shankar (Machine Learning Engineer): Debugging Machine Learning in Production
18:35 Q&A
18:50 Virtual Hugs and Kisses ⊂(◉‿◉)つ

Talk Summary:

Machine learning pipelines can successfully demonstrate high performance on train and evaluation datasets, but what happens after you promote that model to production?

What are some of the challenges faced, and how do groups of different stakeholders with different technical abilities collaborate to identify and “fix” bugs?

In my talk, I will draw from my experiences at an applied ML startup to describe a high level overview of modern ML infrastructure, criteria for promoting models, case studies of “bugs” encountered when clients were interacting with the live ML predictions, and the challenges in solving these issues.

About the speaker:

Twitter: https://twitter.com/sh_reya?s=20
Shreya is a Computer Scientist living in San Francisco interested in making machine learning work in the “real world.” Currently, she is taking a break from work, but previously, she was the first ML engineer at Viaduct, did ML research at Google Brain, and completed her BS and MS in computer science at Stanford.

NLP Zurich:

Meetup.com: https://www.meetup.com/NLP-Zurich/
Linkedin: https://www.linkedin.com/company/nlp-zurich
YouTube: https://www.youtube.com/channel/UCLLX-5j9UNYassOwS0nveDQ
Twitter: https://twitter.com/nlp_zurich