What is Generative Adversarial Networks (GANs)?

Skill Level:

Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.

Other Definitions

Evolutionary Computation is a branch of AI inspired by biological evolution and natural selection. It involves using algorithms to mimic evolutionary processes such as…
Variational Autoencoders are a type of generative model used in unsupervised learning. VAEs learn a low-dimensional representation of input data and can generate new…
Sentiment Analysis is an AI technique that analyses emotions and opinions expressed in text data. Sentiment analysis can classify text as positive, negative, or…