GANs learn a probability distribution of a dataset by pitting two neural networks against each other. One neural network, called the Generator, generates new data instances, … See more

Let’s dig a little deeper and understand how it works mathematically. Discriminator’s job is to perform Binary Classification to detect between Real and Fake so its loss function is Binary Cr… See more

This dataset is great for training and testing models for face detection, particularly for recognizing facial attributes such as finding people with brown hair, are smiling, or wearing gla… See more

Unsupervised learning is the next frontierin artificial intelligence and we are moving towards it. GANs and generative models general are very fun and perplexing. They encapsulat… See more