What kind of models can AWS Deep Learning AMIs help to build?

AWS Deep Learning AMIs (Amazon Machine Images) are specifically designed to facilitate the creation, training, and deployment of deep learning models across a variety of applications. These images come prepackaged with popular deep learning frameworks like TensorFlow, PyTorch, and MXNet, enabling practitioners to build sophisticated models that are capable of handling complex tasks such as image classification, object detection, natural language processing, and more.

The rationale for the selection of this answer lies in the inherent capabilities of deep learning models. Unlike classic regression models or simple linear models, which are foundational but limited in their application, deep learning models excel in automatically discovering patterns and representations from large datasets. This makes them highly effective for tasks requiring high-level abstractions, such as processing images or understanding human language.

The other options either focus on simpler modeling techniques or suggest that deep learning capabilities are not part of the package, which does not align with the primary function of the AWS Deep Learning AMIs. Hence, the choice points directly towards the advanced capabilities these AMIs offer for a range of modern applications in AI and machine learning.