Amazon SageMaker is an AWS-managed service that provides machine learning services. It provides an integrated Jupyter Notebook. Data scientists can easily access data, analyze and extract its features, train a machine learning model, evaluate it, and deploy it on a hosted environment. It provides native support for making our own machine learning algorithms and some commonly used algorithms that perform well on huge datasets.
In this Cloud Lab, you’ll make a notebook instance in Amazon SageMaker, deploy a machine learning model on the notebook instance, and host the model on an endpoint. Moreover, you’ll use a Lambda function to access the endpoint. At the end of the Cloud Lab, you’ll use an API gateway to trigger the Lambda function with a payload and get predictions in response.
The following is the high-level architecture diagram of the infrastructure you’ll create in this Cloud Lab:
