This virtual group (until it is safe to meet in person) is for data scientists, machine learning developers, MLOps engineers and open source enthusiasts who want to expand their knowledge of Kubeflow, the machine learning toolkit for Kubernetes.
- Are you interested in speaking at a future Meetup? - Is your company interested in sponsoring a Meetup? - Would you like to be a co-organizer of a local Meetup?
Contact the Meetup organizers!
This Meetup is sponsored by Arrikto, a leading Kubeflow contributor and developer of MLOps tools.
Zoom Link https://us06web.zoom.us/webinar/register/WN_MrUra4DLSjWBt_F8XtXaWQ
Welcome, Announcements & Housekeeping
Talk #1: Intro to Kubeflow -- Jimmy Guerrero
Talk #2: Title TBD -- Waleed Ayoub
Talk #3: A Deep-Dive Into Declarative AutoML on Kubernetes -- Tomer Sagi
Intro to Kubeflow
Co-organizer, Jimmy Guerrero will give a 10-min, broad overview of the open source Kubeflow MLOps platform. We'll cover architecture, components, distributions and installation options.
Waleed Ayoub was recently the CTO at Rubikloud, a machine learning enterprise software company that was acquired by Kinaxis in 2020, where he spent 2 years as an SVP of product development.
A Deep-Dive Into Declarative AutoML on Kubernetes
When dealing with ever-increasing requirements and growing numbers of models, data scientists may often turn to AutoML as a solution for
minimizing technical debt and optimizing the time and effort required to train and deploy models to production. In this session, Software Engineer Tomer Sagi will introduce the theory behind AutoML and the various different techniques for optimizing your model's algorithm and hyper-parameters. Furthermore, he will discuss how AutoML can be applied to other areas of the machine learning process in what makes an end-to-end ML system.
Tomer is the founder of Metaprov and was a senior developer most recently at HPE where he designed and developed a file system services as part of HPE storage products.