Generative Adversarial Networks, abbreviated as GANs, represent an innovative approach to generative modeling, leveraging deep-learning techniques like convolutional neural networks. Generative modeling, a crucial aspect of unsupervised learning in the realm of machine learning, focuses on automatically discerning and learning the regularities and patterns within input data. The goal is to enable the model to generate or output new instances that are convincingly similar to those from the original dataset.
