What is Variational Autoencoders (VAE)?

Skill Level:

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 data samples similar to the training data. They have applications in tasks such as image generation, anomaly detection, and data compression.

Other Definitions

Regression Analysis is a statistical technique used to determine the relationship between independent variables and a dependent variable. By analysing historical data, businesses can…
Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used…
istributed Computing refers to the use of multiple computers or servers to perform computational tasks in a networked environment. It enables businesses to process…
Machine Learning is a powerful branch of Artificial Intelligence (AI) that focuses on enabling computer systems to learn and improve from experience without being…