Deep learning models are a subset of machine learning that use artificial neural networks to analyze and interpret complex data. These models are designed to automatically learn patterns from large amounts of data, making them effective for tasks such as image recognition, natural language processing, and speech recognition. The architecture of deep learning models typically consists of multiple layers, allowing them to process information in a hierarchical manner. Each layer extracts different features from the input data, enabling the model to make accurate predictions or classifications. Popular frameworks for building these models include TensorFlow and PyTorch.