Abstract: 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
Bio: Yuval Fernbach is the Co-founder & CTO of Qwak, where he is focused on building next-generation ML Infrastructure for ML teams of various sizes. Before Qwak, Yuval was an ML Specialist at AWS , where he helped AWS Customers across EMEA with their ML challenges. Previous to that, he was the CTO of the IT department of the IDF ("Mamram").