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The rapidly evolving landscape of Machine Learning and Large Language Models demands efficient scalable ways to run distributed workloads to train, fine-tune and serve models. Ray is an Open Source framework that simplifies distributed machine learning, and Kubernetes streamlines deployment. In this introductory talk, we'll uncover how to combine Ray and Kubernetes for your ML projects. You will learn about: - Basic Ray concepts (actors, tasks) and their relevance to ML - Setting up a simple Ray cluster within Kubernetes - Running your first distributed ML training job
Abdel Sghiouar is a senior Cloud Developer Advocate @Google Cloud. A co-host of the Kubernetes Podcast by Google and a CNCF Ambassador. His focused areas are GKE/Kubernetes, Service Mesh and Serverless.
Mofizur Rahman (@moficodes) is a Developer Advocate at Google. His favorite programming language these days is Go. He is a strong believer of the power of open source and importance of giving back to the community. He is a self proclaimed sticker collecting addict and has collected... Read More →
