Wednesday, August 24
11:30 AM - 12:00 PM
Spotify started evaluating managed Ray infrastructure as a distributed computing platform that enables ML research and experimentation for non-standardized ML workflows. Ray and its ecosystem provide researchers and data scientists at Spotify with a better model development experience, instant access to distributed computing, and a more expressive programming interface. These features greatly complement our existing production ML workflow.
In this talk, we will share the story of how Ray started at Spotify, how we built and managed our Ray infrastructure, how Ray has been integrated with Spotify's internal infrastructure, and various best practices we have learned along this journey. Finally, we will also showcase some ML applications our users have built with the help of Ray during our evaluation.
Keshi Dai is a machine learning infrastructure engineer at Spotify.
David Xia is a machine learning infrastructure engineer at Spotify.
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