What characterizes Deep Learning (DL)?

Deep Learning is characterized by its utilization of multilayer neural networks for automatic feature learning. This approach allows the system to learn complex representations of data without the need for manual feature selection. Each layer in a deep neural network extracts features at different levels of abstraction, enabling the model to build a hierarchical understanding of the input data. As a result, deep learning models can capture intricate patterns and relationships that may be missed by simpler algorithms.

In contrast to the other options, which suggest either basic algorithmic approaches, single-layer data focus, or manual intervention in feature selection, deep learning automates these processes. This capacity to handle vast amounts of data and discover patterns autonomously is what makes deep learning particularly powerful in applications like image recognition, natural language processing, and, increasingly, in the field of dentistry for diagnostics and treatment planning.