With SageMaker, we just need to make an API call using a Python SDK. SageMaker will launch ECS instances, run model training, persist the training artifacts to S3, and then shut down the EC2 instances automatically. Even in deployment, SageMaker helps automate things. Another API call will create EC2 instances and networking rules to access the model over the internet. — INTRODUCTION SageMaker is AWS’s fully managed service for building and deploying machine learning models in production. Developers can use SageMaker to label and prepare data, choose an algorithm, train, tune and optimize models, and deploy them to the cloud on scale.