Deep learning heavily depends on a vast variety of neural network architectures to achieve complex tasks. Popular architectures include Convolutional Neural Networks (CNNs) for pattern recognition, Recurrent Neural Networks (RNNs) for sequential data processing, and Transformer networks for text comprehension. The decision of architecture relies on