MLOps 2.0 From research centric to production first

MLOps needs no introduction.

MLOps 2.0 is the much awaited next phase to make ML really happen.

In a nutshell it's a comprehensive approach to the ML pipeline that makes sure each stage of the model pipeline is ready for and in production.

If your models are doing great in experimentation but you are still trying to put all the production pieces together, this session might help you understand what's going wrong and how to fix it.

By working according to this methodology data scientists can iterate rapidly which is at the core of a successful ML project.

Join Yuval Fernbach, Co-founder and CTO at Qwak to learn how to:

- Build a feature pipeline that can run in production

- Maintain a centralized production focused model registry

- Monitor, track and react in your production ML environment

Yuval Fernbach

Yuval Fernbach

CTO & Co-founder

MLOps 2.0 From research centric to production first


Brand Leaders are Talking About Qwak

Oren Neiberg
Machine Learning Engineer
“With Qwak we were able to improve our ML delivery dramatically.”

or hiltch
Or Hiltch
VP of Engineering
“Using Qwak allowed us to focus on creating a business impact rather than spending valuable time on our infrastructure setup.”
Jonathan Yaniv
Data Science Leader
“We love Qwak because it provides a unified, end-to-end solution for managing ML-based applications in production.”