GENERATIVE LEARNING Generative learning is an approach to machine learning and artificial intelligence (AI) that focuses on creating models that can generate new data samples that are similar to the training data they were trained on. It involves learning the underlying structure and patterns of the training data and using that knowledge to generate new, previously unseen data. Generative learning is different from discriminative learning, which is another popular approach in machine learning. Discriminative learning focuses on learning the boundaries or decision boundaries between different classes or categories of data. In contrast, generative models aim to capture the probability distribution of the training data and use that distribution to generate new samples. Generative models can be used for various tasks, such as data synthesis, data augmentation, image generation, text generation, and anomaly detection. Some popular generative models include Generative Adversarial ...