Understanding Generative Adversarial Networks

Generative adversarial networks are a way of generating synthetic data that can be used for training AI models. One of the biggest challenges faced while training and creating an effective AI strategy is the time and cost required to gather data and train the AI models. Generative adversarial networks (GANs) can help overcome this challenge of training AI models. GANs are a way of training generative models that can generate new synthetic data based on existing training datasets. The synthetic data can be used for training AI models to reduce the loss functions and improve their accuracy, eliminating the need for a huge volume of training data.