![](https://play.vidyard.com/Bowi7Fw6wdMB1oD8yxb4oE.jpg)
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.
![](https://pages.awscloud.com/rs/112-TZM-766/images/learning-objective.png)
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
![](https://pages.awscloud.com/rs/112-TZM-766/images/who-attend.png)
Who Should Attend?
Developers, DevOps, Data Engineers, Data Scientists
Speakers
- Shashank Prasanna, Sr. Technical Evangelist, AWS
![](https://pages.awscloud.com/rs/112-TZM-766/images/speakers.png)
Learn More
To learn more about the services featured in this talk, please visit:
https://aws.amazon.com/machine-learning/containers
Intro body copy here about 2018 re:Invent launches.
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