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

Backpropagation is a technique used in training Artificial Neural Networks. It involves propagating error information backward through the network, allowing adjustments to be made…
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…
A convolutional neural network is a powerful deep learning model designed for processing and analysing visual data. It excels in tasks such as image…
Cloud computing provides on-demand access to shared computing resources, including storage, processing power, and software applications, over the internet. By leveraging cloud computing, businesses…