How to Build Custom Docker Images For AWS SageMaker

AWS SageMaker extensively uses Docker containers to allow users to train and deploy models. Docker technology allows developers and data scientists to package their projects into standardized units that run consistently on any platform that supports docker. When developing a model in AWS SageMaker, you can build custom Docker images for the training code and the inference code, or combine them into a single Docker image. AWS SageMaker provides an excellent interface for running custom docker images on GPU instances. It handles starting and terminating the instance, placing and running the docker image on it, customizing the instance, stopping conditions, metrics, training data, and algorithm hyperparameters. This tutorial will walk you through how to build custom Docker images for AWS SageMaker and then store them in Amazon Elastic Container Registry (Amazon ECR). To read the article, visit: https://saturncloud.io/blog/how-to-build-custom-docker-images-for-aws-sagemaker/