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.
Transfer Learning is a technique that allows AI models to apply knowledge gained from one task to another related task. By leveraging pre-trained models…