Technical requirements
In this chapter, we will provide code walk-through samples, so you can develop practical skills. The full code examples are available at https://github.com/PacktPublishing/Accelerate-Deep-Learning-Workloads-with-Amazon-SageMaker/blob/main/chapter6/.
To follow along with this code, you will need to have the following:
- An AWS account and IAM user with the permissions to manage Amazon SageMaker resources.
- A SageMaker Notebook, SageMaker Studio Notebook, or local SageMaker-compatible environment established.
- Access to GPU training instances in your AWS account. Each example in this chapter will provide a recommended instance type to use. It’s possible that you will need to increase your compute quota for SageMaker Training Job to have GPU instances enabled. In that case, please follow the instructions at https://docs.aws.amazon.com/sagemaker/latest/dg/regions-quotas.html.