Abstract: 

MLRun is an open-source MLOps orchestration framework. It exists to accelerate the integration of AI/ML applications into existing business workflows. MLRun introduces Data Scientists to a simple Python SDK that transforms their code into a production-quality application. It does so by abstracting the many layers involved in the MLOps pipeline. Developers can build, test, and tune their work anywhere and leverage MLRun to integrate with other components of their business workflow.

The capabilities of MLRun are extensive, and we will cover the basics to get you started. You will leave this session with enough information to:

Get you started with MLRun, on your own, in 10 minutes, so you can automate and accelerate your path to production
Run local move to Kubernetes
Understand how your Python code can run as a Kubernetes job with no code changes
Track your experiments
Get an introduction to advanced MLOps topics using MLRun

Bio: 

Marcelo Litovsky is an experienced Information Technology professional with 30 years of diverse background in Enterprise Architecture, AI, Systems and Database Management, and Programming. He has worked in multiple industries: Financial Services, Entertainment, and Information Technology in his career. Today, he serves as Director of Sales Engineering at Iguazio, bringing his expertise to help Data Scientists, Data Engineers, and Systems Engineers work together to deploy AI/ML applications faster, more efficiently and in a reproducible way. When he is not installing software, talking to customers, or writing Python code, you can find him at the gym or preparing healthy vegan meals.