5 GANs Concepts You Should Know About in 2023 - MarkTechPost

Generative modeling is an unsupervised learning task involving automatically discovering and learning the patterns in input data so that the model can generate new outputs that plausibly could have been drawn from the original dataset. GANs are generative models that can create new data points resembling the training data. For instance, GANs can produce pictures resembling photographs of human faces, even though the faces depicted do not correspond to any actual individual. GANs consist of two models – a generator and a discriminator. The discriminator is a Convolutional Neural Network (CNN) consisting of various hidden layers and one output layer. The generator is an Inverse Convolutional Neural Net doing exactly the opposite of what a CNN does because.