Which AWS service is specifically designed for building and training machine learning models?

The option that focuses specifically on building and training machine learning models is Amazon SageMaker. This service offers a comprehensive set of tools and capabilities aimed at simplifying the development and deployment of machine learning applications. It provides built-in algorithms, pre-built Jupyter notebooks for data exploration, and the ability to easily manage training jobs at scale. SageMaker enables users to quickly train models with labeled data by leveraging its fully managed infrastructure, which can significantly accelerate the machine learning development process.

In contrast, while Amazon S3 is a storage service that can be used to hold your training data, it does not provide functionalities for model building or training. AWS Glue serves as a data preparation service that assists with data extraction, transformation, and loading (ETL) but is not specifically tailored for machine learning model development. Amazon EC2 offers virtual servers for compute capacity and can be used for running machine learning workloads, but it lacks the dedicated tools and streamlined processes found in SageMaker that are essential for efficiently building and training models.