AWS recommends that we use SageMaker as the main platform for ML. With SageMaker, we can define our model to train parameters and hyperparameters. We can also store the model to deploy it later either on the cloud or on-premise. The basic idea of SageMaker is to train the model that is coding it on Jupyter and later deploy the model as a microservice to get the results during normal operation. A high level of computation is required during training.