Broadcast Date: September 30, 2019

Level: 300

With different versions of frameworks, libraries, and drivers for CPUs and GPUs, developers and data scientists spend a lot of time ensuring deep learning software stacks work well together during upgrades and system changes. In this tech talk, we'll take a look at how container technologies can address these challenges by providing training and inference environments that are lightweight, portable, consistent, and scalable. Through code examples, we'll take a closer look at how to integrate AWS Deep Learning Containers into your development and deployment workflows, as well as how to run large scale deep learning workloads on Amazon EKS.

Learning Objectives

  • Understand how containers can help address challenges in deploying deep learning environments
  • Learn about how to use AWS Deep Learning Containers
  • Take away code samples to help you get started quickly

Who Should Attend?

Developers, DevOps, Data Engineers, Data Scientists


  • Shashank Prasanna, Sr. Technical Evangelist, AWS

Learn More

To learn more about the services featured in this talk, please visit:

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Service How To

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Data Lakes & Analytics

Webinar 1:

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December 10th, 2018 | 11:00 AM PT


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Webinar 2:

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December 12th, 2018 | 11:00 AM PT


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