introduce
GAN is a method of generative modeling using deep learning methods such as CNN (Convolutional Neural Network). Generative modeling is an unsupervised learning method that involves automatically discovering and learning patterns in input data so that the model can be used to generate new examples from the original dataset.
GAN is a method for training generative models by framing the problem as a supervised learning problem with two sub-models. GAN has two components:
- Generator: It is trained to generate new datasets, for example in computer vision it generates new images from existing real world images.
- Discriminator: It compares these images to some real-world examples and classifies real and fake images.