September 27, 2021

Leverage the Power of AWS Deep Learning Containers with Kubernetes for Training Deep Learning Models at Scale

Broadcast Date: September 27, 2021 Level: 300 Are you looking to learn how to deploy your ML workflows in the cloud using Kubernetes? In this tech talk, we’ll take you on a MLOps journey so you can discover how to train and host ML models at scale using AWS Deep Learning Containers (DLCs). DLCs provide a set of regularly updated libraries and packages to train and serve models in TensorFlow, PyTorch, or MXNet. You will also learn about the benefits of using DLCs with Amazon Elastic Kubernetes Service (EKS) and learn how to get started with production training and inference workflows. Learn about AWS Deep Learning Containers (DLCs) Learn how you can customize your MLOps workflow with Deep Learning containers Get started with AWS DLCs to train and host models on Amazon Elastic Kubernetes Service (EKS) MLOps, ML Practitioners, Data Scientists

Arjuna Keshavan, Software Dev Engineer, AWS Naina Prasad, Technical Program Manager, AWS

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