Ray & KubeRay, with Richard Liaw and Kai-Hsun Chen
Kubernetes Podcast from Google
00:00
Exploring the Ray Project
This chapter delves into the origins and evolution of the Ray project, originally developed from UC Berkeley's work in distributed deep learning. Speakers share their personal journeys and experiences with Ray, illustrating its integration capabilities across various engineering disciplines, particularly in machine learning and data science. The chapter emphasizes Ray's advantages in enhancing developer productivity, efficient data processing, and its unique functionalities compared to other solutions like Kubeflow and Dask.
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