Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.
Adversarial machine learning involves studying and defending AI models against attacks or adversarial examples designed to deceive the system. By understanding vulnerabilities and deploying…