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

istributed Computing refers to the use of multiple computers or servers to perform computational tasks in a networked environment. It enables businesses to process…
Computer vision is a field of AI that focuses on training machines to understand and interpret images and videos. By analysing visual data, machines…
Support Vector Machines (SVMs) are Machine Learning algorithms used for classification and regression tasks. SVMs create decision boundaries and maximise the margin between different…
Regression Analysis is a statistical technique used to determine the relationship between independent variables and a dependent variable. By analysing historical data, businesses can…