Monday, August 22
1:00 PM - 4:30 PM
An introduction to Ray (https://www.ray.io/), the system for scaling your Python and machine learning applications from a laptop to a cluster. We'll start with a hands-on exploration of the core Ray API for distributed workloads, covering basic distributed Ray Core API patterns, and then move on to a quick introduction to Ray's native libraries:
Level: Beginners or intermediate and new to Ray
Prerequisite knowledge or skills:
Jules S. Damji is a lead developer advocate at Anyscale and an MLflow contributor. He is a hands-on developer with over 20 years of experience and has worked at leading companies such as Sun Microsystems, Netscape, @Home, Opsware/Loudcloud, VeriSign, ProQuest, Hortonworks, and Databricks, building large-scale distributed systems. He holds a BSc and MSc in computer science (from Oregon State University and Cal State, Chico, respectively), and an MA in political advocacy and communication (from Johns Hopkins University).
Come connect with the global community of thinkers and disruptors who are building and deploying the next generation of AI and ML applications.Save your spot