What is the primary purpose of Amazon SageMaker?

The primary purpose of Amazon SageMaker is to facilitate the development, training, and deployment of machine learning models. It provides a comprehensive set of tools that enable developers and data scientists to build scalable machine learning workflows without needing extensive infrastructure management. SageMaker supports various tasks related to machine learning, including data preparation, model training, tuning, and deployment, allowing users to focus on creating high-quality models efficiently.

This platform is designed to streamline the machine learning process. It includes integrated tools for labeling datasets, selecting algorithms, training models with distributed computing power, and deploying those models into a production environment for real-time predictions. By offering these capabilities, SageMaker simplifies the machine learning lifecycle, promoting rapid experimentation and innovation.

Other choices suggest functionalities that do not align with SageMaker's core purpose. Web hosting pertains to hosting websites and web applications, while database storage involves managing data persistently, and content delivery focuses on distributing content to end-users efficiently. These areas do not relate to the specific functionalities that SageMaker offers in the machine learning domain.