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

Object Recognition is the capability of AI systems to identify and classify objects within images or videos. By utilising advanced algorithms and Neural Networks,…
Ethics in AI focuses on the responsible and ethical use of AI technologies. Businesses must consider the fairness, transparency, accountability, and privacy implications of…
Facial Recognition is an AI technology that involves identifying and verifying individuals based on their facial characteristics. It analyses facial features such as the…
An algorithm is a set of rules and instructions that guide AI systems in solving problems or making decisions. Algorithms process data, analyse patterns,…