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.
Ensemble Learning involves combining multiple Machine Learning models to achieve superior performance and accuracy. By leveraging the “wisdom of the crowd,” Ensemble Learning mitigates…